Re: Clement of Alexandria -- A Basic Stylometric Study
Posted: Mon Jun 01, 2015 6:06 pm
Very interesting.
Investigating the roots of western civilization (ye olde BC&H forum of IIDB lives on...)
https://earlywritings.com/forum/
testsize: 4365
$VAR1 = 88; $VAR2 = 29; $VAR3 = 93; $VAR4 = 251; $VAR5 = 99; $VAR6 = 21; $VAR7 = 25; $VAR8 = 31; $VAR9 = 36; $VAR10 = 71; $VAR11 = 19; $VAR12 = 31; $VAR13 = 9; $VAR14 = 7; $VAR15 = 7; $VAR16 = 15; $VAR17 = 22; $VAR18 = 7; $VAR19 = 16; $VAR20 = 23;
20 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ];
Author Z-Score-Based P-Values
$VAR1 = '0.145413047886394'; $VAR2 = '0.000901138623231966'; $VAR3 = '0.0913020235022347';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0121911830943714'; $VAR2 = '0.00121881348131204'; $VAR3 = '0.118188400968307'; $VAR4 = '0.0498318645244918'; $VAR5 = '0.0131940811518082'; $VAR6 = '5.91405231787019e-12'; $VAR7 = '4.34609970100557e-05'; $VAR8 = '0'; $VAR9 = '1.95087693605705e-185'; $VAR10 = '1.68934449840894e-65'; $VAR11 = '1.09867528822474e-11'; $VAR12 = '4.4488774910846e-20'; $VAR13 = '1.47686290317326e-08'; $VAR14 = '0.00169556733417891'; $VAR15 = '0.00214808635364086'; $VAR16 = '0.0394381736188443'; $VAR17 = '0.0169018091435257'; $VAR18 = '5.30710670175691e-09'; $VAR19 = '0.000492395650257427'; $VAR20 = '1.39013748628716e-10'; $VAR21 = '5.18747184360314e-08'; $VAR22 = '9.64828528134546e-05'; $VAR23 = '0.0319428063927732'; $VAR24 = '0.000333708459071205'; $VAR25 = '0.0180331392672953'; $VAR26 = '0.0591573593950859'; $VAR27 = '4.31905406628548e-07'; $VAR28 = '0.028537343187936'; $VAR29 = '0.0235808410796549';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.611966026556588'; $VAR2 = '0.00379241223983408'; $VAR3 = '0.384241561203578';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.551639789986688'; $VAR3 = 3; $VAR4 = '0.448360210013312';
Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0463576158940397
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.955696202531646
Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1
Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
The situation does not improve even if you remove the incipit and the long quote of the 'secret gospel' and add some more 'words' to be counted.testsize: 749
$VAR1 = 14; $VAR2 = 3; $VAR3 = 15; $VAR4 = 45; $VAR5 = 15; $VAR6 = 3; $VAR7 = 4; $VAR8 = 9; $VAR9 = 0; $VAR10 = 5; $VAR11 = 7; $VAR12 = 0; $VAR13 = 3; $VAR14 = 1; $VAR15 = 0; $VAR16 = 2; $VAR17 = 3; $VAR18 = 1; $VAR19 = 4; $VAR20 = 2;
20 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ];
Author Z-Score-Based P-Values
$VAR1 = '0.239955979770313'; $VAR2 = '0.15627245207971'; $VAR3 = '0.21868928826961';
Control Z-Score-Based P-Values
$VAR1 = '0.097729840149245'; $VAR2 = '0.0903563825906666'; $VAR3 = '0.192363798619605'; $VAR4 = '0.265169803857623'; $VAR5 = '0.228744745288692'; $VAR6 = '0.036703429649263'; $VAR7 = '0.0901719041523447'; $VAR8 = '0.0554698680497574'; $VAR9 = '0.109323876919529'; $VAR10 = '0.000566835398378018'; $VAR11 = '0.131945576748502'; $VAR12 = '0.00783067630839334'; $VAR13 = '0.111350069835556'; $VAR14 = '0.104457453482461'; $VAR15 = '0.118129003101242'; $VAR16 = '0.122765927768801'; $VAR17 = '0.153215556560225'; $VAR18 = '0.0859315683074529'; $VAR19 = '0.0629689701000199'; $VAR20 = '0.119123175545919'; $VAR21 = '0.0856285914811254'; $VAR22 = '0.175958863093962'; $VAR23 = '0.13824411417826'; $VAR24 = '0.110578942734896'; $VAR25 = '0.178642716134681'; $VAR26 = '0.240643005597686'; $VAR27 = '0.13530828297217'; $VAR28 = '0.208473672498232'; $VAR29 = '0.151730655959346';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.390224532354717'; $VAR2 = '0.254135548491442'; $VAR3 = '0.35563991915384';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.475042034177885'; $VAR3 = 4; $VAR4 = '0.524957965822115';
Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.695402298850575
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.0919540229885057
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.883211678832117
Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.0833333333333333
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
0.892988929889299
Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.0357142857142857
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.95115103874228
Author Chi-Square-Based P-Values
$VAR1 = '0.897126717178744'; $VAR2 = '0.876686010922532'; $VAR3 = '0.766954128799045';
Control Chi-Square-Based P-Values
$VAR1 = '0.137898770544387'; $VAR2 = '0.263214501782374'; $VAR3 = '0.97251600690767'; $VAR4 = '0.996383635782013'; $VAR5 = '0.995727137880758'; $VAR6 = '0.000948092883388932'; $VAR7 = '0.253210360195565'; $VAR8 = '0.00852822453421988'; $VAR9 = '0.65938916375342'; $VAR10 = 0; $VAR11 = '0.346606811740825'; $VAR12 = '1.0011159413525e-12'; $VAR13 = '0.00377297557020349'; $VAR14 = '0.169854249175826'; $VAR15 = '0.599467656898274'; $VAR16 = '0.493172636244664'; $VAR17 = '0.912577608896469'; $VAR18 = '0.277004254454816'; $VAR19 = '0.00103826061119019'; $VAR20 = '0.149481145224522'; $VAR21 = '0.000251868655303691'; $VAR22 = '0.851018068030414'; $VAR23 = '0.697616764950275'; $VAR24 = '0.442629632622023'; $VAR25 = '0.993407920946543'; $VAR26 = '0.98246524429608'; $VAR27 = '0.118313132250566'; $VAR28 = '0.998364840186754'; $VAR29 = '0.8885746060188';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.353092891912648'; $VAR2 = '0.345047798676054'; $VAR3 = '0.301859309411298';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.473295021385187'; $VAR3 = 28; $VAR4 = '0.526704978614813';
Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0.35632183908046
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0.0188087774294671
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.949860724233983
Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1
Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
The most that can be said is that this doesn't disprove Clementine authorship.testsize: 585
$VAR1 = 9; $VAR2 = 3; $VAR3 = 11; $VAR4 = 31; $VAR5 = 12; $VAR6 = 3; $VAR7 = 4; $VAR8 = 7; $VAR9 = 0; $VAR10 = 5; $VAR11 = 3; $VAR12 = 0; $VAR13 = 3; $VAR14 = 0; $VAR15 = 0; $VAR16 = 1; $VAR17 = 3; $VAR18 = 1; $VAR19 = 4; $VAR20 = 1; $VAR21 = 40; $VAR22 = 30; $VAR23 = 0; $VAR24 = 11; $VAR25 = 3; $VAR26 = 1; $VAR27 = 7; $VAR28 = 3;
28 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ]; $VAR21 = [ 'O', 'OI', 'H', 'AI', 'TO', 'TA' ]; $VAR22 = [ 'TOU', 'TWN', 'THS' ]; $VAR23 = [ 'TWi', 'TOIS', 'THi', 'TAIS' ]; $VAR24 = [ 'TON', 'TOUS', 'THN', 'TAS' ]; $VAR25 = [ 'OUTOS', 'TOUTOU', 'TOUTWi', 'TOUTON', 'AUTOI', 'TOUTWN', 'TOUTOIS', 'TOUTOUS', 'AUTH', 'TAUTHS', 'TAUTHi', 'TAUTHN', 'AUTAI', 'TAUTAIS', 'TAUTAS', 'TOUTO', 'TOUTO', 'TAUTA' ]; $VAR26 = [ 'TE' ]; $VAR27 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR28 = [ 'DIA', 'DI' ];
Author Z-Score-Based P-Values
$VAR1 = '0.238966466484185'; $VAR2 = '0.180860494019055'; $VAR3 = '0.178908540891056';
Control Z-Score-Based P-Values
$VAR1 = '0.109399101885252'; $VAR2 = '0.0870618496838642'; $VAR3 = '0.157635860502871'; $VAR4 = '0.271300166643239'; $VAR5 = '0.168735908605299'; $VAR6 = '0.0330976885518663'; $VAR7 = '0.0439533347287748'; $VAR8 = '0.11798577811795'; $VAR9 = '0.101263307889919'; $VAR10 = '0.00142063415628147'; $VAR11 = '0.126728996972072'; $VAR12 = '0.0124400065499432'; $VAR13 = '0.0971078780086916'; $VAR14 = '0.116118473265528'; $VAR15 = '0.112225272240502'; $VAR16 = '0.0945957842924575'; $VAR17 = '0.182692612311113'; $VAR18 = '0.0750775225264509'; $VAR19 = '0.0611908075683004'; $VAR20 = '0.113578531394736'; $VAR21 = '0.0847478969047339'; $VAR22 = '0.135621238987263'; $VAR23 = '0.0901770694789485'; $VAR24 = '0.124684537842573'; $VAR25 = '0.18824496566581'; $VAR26 = '0.205067999901377'; $VAR27 = '0.0966427618490444'; $VAR28 = '0.200584311062807'; $VAR29 = '0.104617619995548';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.399118585632045'; $VAR2 = '0.302070770144545'; $VAR3 = '0.29881064422341';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.468316858226766'; $VAR3 = 4; $VAR4 = '0.531683141773234';
Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.757847533632287
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.0943856794141578
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.889249001365763
Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1
Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.0555555555555556
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.931699846860643
Author Z-Score-Based P-Values
$VAR1 = '0.175632194388122'; $VAR2 = '0.0273226233915555'; $VAR3 = '0.0581206776989506';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.02782059302406'; $VAR2 = '0.00143590353354502'; $VAR3 = '0.0562975433097471'; $VAR4 = '0.137281471036673'; $VAR5 = '0.0513706697595692'; $VAR6 = '7.3655989200826e-09'; $VAR7 = '5.53219519454619e-06'; $VAR8 = '5.57131947192697e-28'; $VAR9 = '4.69322834774578e-184'; $VAR10 = '7.34148182893381e-28'; $VAR11 = '0.0450709140156383'; $VAR12 = '2.39311758232927e-11'; $VAR13 = '0.0142592416277771'; $VAR14 = '0.0342824655640593'; $VAR15 = '0.0809509758911259'; $VAR16 = '0.0307824505324834'; $VAR17 = '0.0794659503371223'; $VAR18 = '0.00240605043289266'; $VAR19 = '0.000381490029783153'; $VAR20 = '0.000180597952357559'; $VAR21 = '2.06575862837364e-05'; $VAR22 = '0.00371250716450203'; $VAR23 = '0.0349457220931891'; $VAR24 = '0.0149668300751288'; $VAR25 = '0.027841794237935'; $VAR26 = '0.101402935447586'; $VAR27 = '0.000445600243109259'; $VAR28 = '0.0803367537675786'; $VAR29 = '0.0237382690533745';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.672725695937631'; $VAR2 = '0.104654109116848'; $VAR3 = '0.222620194945521';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.56128003917532'; $VAR3 = 4; $VAR4 = '0.43871996082468';
Author Z-Score-Based P-Values
$VAR1 = '0.107237611670189'; $VAR2 = '0.0286922493008972'; $VAR3 = '0.047443351245165';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.00666168380760475'; $VAR2 = '0.00922277109137771'; $VAR3 = '0.0946030528784022'; $VAR4 = '0.0756709010836628'; $VAR5 = '0.00448245294473958'; $VAR6 = '1.46379030258297e-10'; $VAR7 = '8.89074884869157e-07'; $VAR8 = '5.49790383615881e-27'; $VAR9 = '8.45603081909304e-215'; $VAR10 = '2.37539157284602e-29'; $VAR11 = '0.00459961966469155'; $VAR12 = '6.80016274498375e-15'; $VAR13 = '0.0121051010844485'; $VAR14 = '0.00771373778319094'; $VAR15 = '0.0209650467794752'; $VAR16 = '0.0243188214625438'; $VAR17 = '0.0714454958850729'; $VAR18 = '0.000151037766570767'; $VAR19 = '0.0028847489834993'; $VAR20 = '9.7450111833517e-07'; $VAR21 = '4.04850190277198e-06'; $VAR22 = '0.000598177410150459'; $VAR23 = '0.0433457634106286'; $VAR24 = '0.00469730414614475'; $VAR25 = '0.0264803134684096'; $VAR26 = '0.064698057857405'; $VAR27 = '8.38764669458983e-06'; $VAR28 = '0.0624867640809138'; $VAR29 = '0.0386274976616659';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.584805219770727'; $VAR2 = '0.156469142652421'; $VAR3 = '0.258725637576853';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.531298348179846'; $VAR3 = 3; $VAR4 = '0.468701651820154';
Author Z-Score-Based P-Values
$VAR1 = '0.0824682709412135'; $VAR2 = '0.00415072678535048'; $VAR3 = '0.0187909211667257';
Good match. Z-Score-Based P-Value > 0.05.
Control Z-Score-Based P-Values
$VAR1 = '0.0389219731744169'; $VAR2 = '0.0003349616659174'; $VAR3 = '0.0342253859865855'; $VAR4 = '0.0183701688572872'; $VAR5 = '0.00597865831662005'; $VAR6 = '3.92333131016311e-11'; $VAR7 = '2.13610617664352e-10'; $VAR8 = '3.76665695464297e-15'; $VAR9 = '1.2732853591179e-257'; $VAR10 = '9.28539727412726e-52'; $VAR11 = '3.23230923980392e-05'; $VAR12 = '1.53666755200642e-23'; $VAR13 = '0.00119991028336151'; $VAR14 = '0.00914552955304082'; $VAR15 = '0.0270038887302336'; $VAR16 = '0.028166406661062'; $VAR17 = '0.053595433790182'; $VAR18 = '2.10481254546187e-05'; $VAR19 = '0.00265770638746398'; $VAR20 = '2.4750826562569e-08'; $VAR21 = '5.77367602095181e-06'; $VAR22 = '5.36635825253591e-05'; $VAR23 = '0.0406304006242715'; $VAR24 = '0.000412424312074317'; $VAR25 = '0.013711113765813'; $VAR26 = '0.035887261186336'; $VAR27 = '5.31144381825819e-07'; $VAR28 = '0.0250959668833924'; $VAR29 = '0.018836078848505';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.782357787645194'; $VAR2 = '0.0393770038809385'; $VAR3 = '0.178265208473867';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.606100437320995'; $VAR3 = 17; $VAR4 = '0.393899562679005';
Author Z-Score-Based P-Values
$VAR1 = '0.110505697189735'; $VAR2 = '0.00748399482117353'; $VAR3 = '0.0611989383310658';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0267588410461724'; $VAR2 = '0.00148898973648727'; $VAR3 = '0.0708441011321246'; $VAR4 = '0.0756945198806317'; $VAR5 = '0.0011920579033652'; $VAR6 = '1.43073955047932e-08'; $VAR7 = '9.97631933544808e-06'; $VAR8 = '7.53174870767207e-10'; $VAR9 = '2.05888736666225e-206'; $VAR10 = '4.04857688592491e-107'; $VAR11 = '1.74483448605373e-05'; $VAR12 = '7.98025186440753e-15'; $VAR13 = '0.0015908691420342'; $VAR14 = '0.00623029755574913'; $VAR15 = '0.00363462025473137'; $VAR16 = '0.00946516184224697'; $VAR17 = '0.0285526958293264'; $VAR18 = '6.566063003799e-08'; $VAR19 = '0.000508312911662489'; $VAR20 = '6.14159775089668e-07'; $VAR21 = '1.76996420171829e-06'; $VAR22 = '9.78404536893078e-05'; $VAR23 = '0.0174421810615398'; $VAR24 = '0.00665264480319697'; $VAR25 = '0.0219566166244337'; $VAR26 = '0.0774009201533712'; $VAR27 = '9.94921262971493e-05'; $VAR28 = '0.0420291584419999'; $VAR29 = '0.0472926066675885';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.616700384275718'; $VAR2 = '0.0417660138753815'; $VAR3 = '0.3415336018489';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.588088374705604'; $VAR3 = 26; $VAR4 = '0.411911625294396';
Author Z-Score-Based P-Values
$VAR1 = '0.164792909897107'; $VAR2 = '0.00760488018849116'; $VAR3 = '0.0673888011239041';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.023468038624533'; $VAR2 = '0.00749130426931931'; $VAR3 = '0.0572563341476108'; $VAR4 = '0.0680963477880058'; $VAR5 = '0.0108787884338907'; $VAR6 = '7.31342952576999e-09'; $VAR7 = '1.91002559491324e-07'; $VAR8 = '2.35156862199798e-08'; $VAR9 = '6.86730217887237e-234'; $VAR10 = '3.80292747137152e-87'; $VAR11 = '0.0268106999086168'; $VAR12 = '3.40164364827471e-15'; $VAR13 = '0.00196760327485455'; $VAR14 = '0.00969108704187161'; $VAR15 = '0.0254228285349839'; $VAR16 = '0.015421520521892'; $VAR17 = '0.0633911621733293'; $VAR18 = '3.02657136991658e-06'; $VAR19 = '6.1521085403499e-05'; $VAR20 = '1.99848870657279e-08'; $VAR21 = '8.7881056958383e-06'; $VAR22 = '0.000442141462464159'; $VAR23 = '0.0208185841403742'; $VAR24 = '6.40420543723858e-05'; $VAR25 = '0.00883412619936611'; $VAR26 = '0.0527926556411981'; $VAR27 = '0.00153265912802022'; $VAR28 = '0.0375380050831736'; $VAR29 = '0.0241730962815983';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.687248227959197'; $VAR2 = '0.0317152020475022'; $VAR3 = '0.2810365699933';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.707602023103709'; $VAR3 = 4; $VAR4 = '0.292397976896291';
Author Z-Score-Based P-Values
$VAR1 = '0.111189725817848'; $VAR2 = '0.000845600059691961'; $VAR3 = '0.0422350494237638';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0229339536983116'; $VAR2 = '0.00888533667285483'; $VAR3 = '0.0394333192376367'; $VAR4 = '0.0657086154664528'; $VAR5 = '0.0122378536651146'; $VAR6 = '2.61569854993523e-11'; $VAR7 = '6.69161351099993e-08'; $VAR8 = '2.83756722376003e-319'; $VAR9 = '3.22388100936173e-167'; $VAR10 = '1.11451195468968e-71'; $VAR11 = '0.020186824935264'; $VAR12 = '2.77423960941059e-14'; $VAR13 = '0.00223621536974783'; $VAR14 = '0.0285484977309586'; $VAR15 = '0.0421428132162825'; $VAR16 = '0.014833802838586'; $VAR17 = '0.0681405557451809'; $VAR18 = '0.000421100408442739'; $VAR19 = '0.0001080681088237'; $VAR20 = '8.19479176409627e-09'; $VAR21 = '8.13360135333622e-07'; $VAR22 = '5.57483226888127e-05'; $VAR23 = '0.0320242461619289'; $VAR24 = '1.0273410564072e-06'; $VAR25 = '0.025884931004085'; $VAR26 = '0.0280163611294132'; $VAR27 = '2.66974262965076e-05'; $VAR28 = '0.0202517252924613'; $VAR29 = '0.00543958627510071';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.720745804894066'; $VAR2 = '0.00548128607349551'; $VAR3 = '0.273772909032438';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.620027609663726'; $VAR3 = 17; $VAR4 = '0.379972390336273';
Author Z-Score-Based P-Values
$VAR1 = '0.0642111781138632'; $VAR2 = '0.00171045823223661'; $VAR3 = '0.0262683792041696';
Good match. Z-Score-Based P-Value > 0.05.
Control Z-Score-Based P-Values
$VAR1 = '0.00318373458339036'; $VAR2 = '0.00173855032088974'; $VAR3 = '0.0406571725602829'; $VAR4 = '0.0626892003297425'; $VAR5 = '0.0204993894071774'; $VAR6 = '8.6732028754175e-11'; $VAR7 = '2.20942891016228e-08'; $VAR8 = '0'; $VAR9 = '6.91868498042178e-198'; $VAR10 = '4.57198095250288e-95'; $VAR11 = '0.0003071947532923'; $VAR12 = '3.18816436108696e-16'; $VAR13 = '0.000386262698552709'; $VAR14 = '0.0156242059972711'; $VAR15 = '0.0231832109020983'; $VAR16 = '0.0202811440292099'; $VAR17 = '0.0492366831245109'; $VAR18 = '0.000572122742976243'; $VAR19 = '9.85928119304763e-05'; $VAR20 = '2.09728807677249e-10'; $VAR21 = '1.52370195834476e-06'; $VAR22 = '2.42475148711906e-05'; $VAR23 = '0.0207737786880624'; $VAR24 = '7.97473750372443e-08'; $VAR25 = '0.0148983622868027'; $VAR26 = '0.0232820621036027'; $VAR27 = '5.59564607651031e-06'; $VAR28 = '0.0211146789481579'; $VAR29 = '0.00915442903199711';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.69650902790932'; $VAR2 = '0.0185536169185689'; $VAR3 = '0.284937355172111';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.505996742495126'; $VAR3 = 4; $VAR4 = '0.494003257504874';
Author Z-Score-Based P-Values
$VAR1 = '0.114069128558597'; $VAR2 = '0.000211773752275666'; $VAR3 = '0.0429219384827756';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.023981006118095'; $VAR2 = '0.00450192191987152'; $VAR3 = '0.0677401614979971'; $VAR4 = '0.0814486772075348'; $VAR5 = '0.0227528913120345'; $VAR6 = '1.49939287563297e-14'; $VAR7 = '7.85235818813492e-09'; $VAR8 = '2.71736105212686e-322'; $VAR9 = '4.30014626484274e-191'; $VAR10 = '1.15051097141332e-260'; $VAR11 = '0.0108836335407889'; $VAR12 = '5.14375463919645e-15'; $VAR13 = '0.000425339743850498'; $VAR14 = '0.0132251701372594'; $VAR15 = '0.0154913736920536'; $VAR16 = '0.0187808000880381'; $VAR17 = '0.075004461663421'; $VAR18 = '2.24403725348054e-07'; $VAR19 = '0.000611657482548781'; $VAR20 = '1.50520063005187e-06'; $VAR21 = '4.48382733360271e-05'; $VAR22 = '0.000775985876828896'; $VAR23 = '0.0439394981632955'; $VAR24 = '7.43790486546224e-05'; $VAR25 = '0.0183163824989847'; $VAR26 = '0.0138115026410691'; $VAR27 = '0.000424127477336679'; $VAR28 = '0.033727989915962'; $VAR29 = '0.0129456845039793';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.725617476011961'; $VAR2 = '0.00134713692962871'; $VAR3 = '0.273035387058411';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.583420666530192'; $VAR3 = 4; $VAR4 = '0.416579333469808';
Author Z-Score-Based P-Values
$VAR1 = '0.112738369663818'; $VAR2 = '0.000449551489882513'; $VAR3 = '0.0488870564633003';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0196374267786769'; $VAR2 = '0.0167984666467129'; $VAR3 = '0.0303305891008324'; $VAR4 = '0.0444762499342243'; $VAR5 = '0.0148277488813066'; $VAR6 = '1.53154138579379e-19'; $VAR7 = '1.39407585706268e-09'; $VAR8 = '0'; $VAR9 = '3.48769270905702e-208'; $VAR10 = '1.51179128830293e-138'; $VAR11 = '0.0144677258680161'; $VAR12 = '3.34957490776342e-18'; $VAR13 = '0.000884156524790406'; $VAR14 = '0.00964426731428726'; $VAR15 = '0.0191931377010463'; $VAR16 = '0.0342878507255054'; $VAR17 = '0.0919495746233905'; $VAR18 = '1.21511880282215e-18'; $VAR19 = '0.000362061302497777'; $VAR20 = '2.30204157673836e-10'; $VAR21 = '1.17598339232554e-06'; $VAR22 = '3.75817879417231e-05'; $VAR23 = '0.028263450053101'; $VAR24 = '8.41715298929864e-07'; $VAR25 = '0.0114909436013211'; $VAR26 = '0.0247940148552579'; $VAR27 = '8.44962130265694e-07'; $VAR28 = '0.0386907418899151'; $VAR29 = '0.0068774786367488';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.695593924006146'; $VAR2 = '0.00277372544789022'; $VAR3 = '0.301632350545964';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.550781679186873'; $VAR3 = 17; $VAR4 = '0.449218320813127';
Author Z-Score-Based P-Values
$VAR1 = '0.171093312981604'; $VAR2 = '2.93984516386849e-05'; $VAR3 = '0.0261742602428154';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.017468788308475'; $VAR2 = '0.00209618926795158'; $VAR3 = '0.0377896977118809'; $VAR4 = '0.0705380117864'; $VAR5 = '0.028081682210077'; $VAR6 = '2.05457924427615e-22'; $VAR7 = '4.30162075490204e-08'; $VAR8 = '0'; $VAR9 = '2.97553797309504e-223'; $VAR10 = '6.35647516766444e-297'; $VAR11 = '0.00711000175668741'; $VAR12 = '4.67303879057975e-18'; $VAR13 = '0.000507796144920998'; $VAR14 = '0.00583575640902676'; $VAR15 = '0.0138881858631337'; $VAR16 = '0.00858087300103147'; $VAR17 = '0.0709687827662151'; $VAR18 = '8.44337073916072e-09'; $VAR19 = '0.000100978798859006'; $VAR20 = '2.18809826470324e-09'; $VAR21 = '2.35720243367555e-08'; $VAR22 = '0.000233878173353036'; $VAR23 = '0.0108190182652153'; $VAR24 = '1.51837222498367e-05'; $VAR25 = '0.0439886474468797'; $VAR26 = '0.0837639058544788'; $VAR27 = '5.1748136041113e-07'; $VAR28 = '0.0437603399609289'; $VAR29 = '0.00496119553476288';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.867186716188032'; $VAR2 = '0.000149006096692422'; $VAR3 = '0.132664277715275';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.671330063801907'; $VAR3 = 26; $VAR4 = '0.328669936198093';
Author Z-Score-Based P-Values
$VAR1 = '0.0956755771618791'; $VAR2 = '0.0169869739996606'; $VAR3 = '0.0194407547194331';
Good match. Z-Score-Based P-Value > 0.05.
Control Z-Score-Based P-Values
$VAR1 = '0.00661679827446663'; $VAR2 = '0.00305054344659964'; $VAR3 = '0.0647322321509935'; $VAR4 = '0.0573756525099946'; $VAR5 = '0.00139717503446245'; $VAR6 = '1.79965004338776e-16'; $VAR7 = '2.02142199733767e-08'; $VAR8 = '8.80635785207679e-34'; $VAR9 = '7.79932138211456e-241'; $VAR10 = '2.14537863546996e-36'; $VAR11 = '0.00131156699982828'; $VAR12 = '9.39497203355355e-18'; $VAR13 = '1.65744040944569e-05'; $VAR14 = '0.00198489970207878'; $VAR15 = '0.0046253799657655'; $VAR16 = '0.00572984984393743'; $VAR17 = '0.0729294208195738'; $VAR18 = '3.11592567709835e-05'; $VAR19 = '0.000538960425939253'; $VAR20 = '9.49186286500501e-08'; $VAR21 = '2.20443839505331e-07'; $VAR22 = '0.000132006616553062'; $VAR23 = '0.0394379752156319'; $VAR24 = '0.00398524325338263'; $VAR25 = '0.0204108812699442'; $VAR26 = '0.0655069512584329'; $VAR27 = '5.81521301343538e-06'; $VAR28 = '0.0606773159846999'; $VAR29 = '0.037052977256516';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.724248167173684'; $VAR2 = '0.128588560947643'; $VAR3 = '0.147163271878673';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.567453980055821'; $VAR3 = 17; $VAR4 = '0.432546019944179';
Author Z-Score-Based P-Values
$VAR1 = '0.135078904501818'; $VAR2 = '0.0164330049169535'; $VAR3 = '0.0418255920257736';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.00800234151531736'; $VAR2 = '0.00229489103784224'; $VAR3 = '0.0596047410602183'; $VAR4 = '0.126687136797961'; $VAR5 = '0.00895146756790502'; $VAR6 = '2.62639498177396e-11'; $VAR7 = '1.03631923299016e-10'; $VAR8 = '5.56488435894115e-15'; $VAR9 = '1.81248682539519e-180'; $VAR10 = '1.24069076178567e-81'; $VAR11 = '0.0038523185446857'; $VAR12 = '8.16586345758538e-17'; $VAR13 = '0.000119692616273651'; $VAR14 = '0.00376255793424717'; $VAR15 = '0.0110163045579493'; $VAR16 = '0.00861569118703454'; $VAR17 = '0.0675229482104783'; $VAR18 = '2.42135667078791e-05'; $VAR19 = '0.00010384419987666'; $VAR20 = '4.59554089396257e-08'; $VAR21 = '5.20662392236287e-07'; $VAR22 = '0.000222381780764746'; $VAR23 = '0.0364552955176135'; $VAR24 = '1.75579565835158e-05'; $VAR25 = '0.0237539861646592'; $VAR26 = '0.069422689213621'; $VAR27 = '7.89070448310917e-05'; $VAR28 = '0.0440751072171114'; $VAR29 = '0.018573053969703';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.698668926062244'; $VAR2 = '0.0849964688390627'; $VAR3 = '0.216334605098693';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.516029137435453'; $VAR3 = 4; $VAR4 = '0.483970862564547';
Author Z-Score-Based P-Values
$VAR1 = '0.189525919025166'; $VAR2 = '0.0168636137230183'; $VAR3 = '0.0247732041793049';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.00474757719758126'; $VAR2 = '0.00214473585815616'; $VAR3 = '0.0601935188822396'; $VAR4 = '0.115714909628259'; $VAR5 = '0.000621548139443569'; $VAR6 = '5.05310788978207e-13'; $VAR7 = '4.26046675720424e-07'; $VAR8 = '4.26386380629512e-12'; $VAR9 = '9.21222428850802e-173'; $VAR10 = '1.80161020526088e-29'; $VAR11 = '0.00270512872842512'; $VAR12 = '4.72301914415365e-17'; $VAR13 = '0.000499656106281198'; $VAR14 = '0.00392411287588487'; $VAR15 = '0.0140356089586303'; $VAR16 = '0.0061817613252526'; $VAR17 = '0.0782610357081385'; $VAR18 = '3.49835106627283e-07'; $VAR19 = '0.00118816821926077'; $VAR20 = '7.20131135072874e-08'; $VAR21 = '2.13963017923509e-07'; $VAR22 = '1.14334665597004e-05'; $VAR23 = '0.0276372230801344'; $VAR24 = '0.00413310846205375'; $VAR25 = '0.0622713594047995'; $VAR26 = '0.143895610573104'; $VAR27 = '4.39497771153755e-07'; $VAR28 = '0.0758625428199919'; $VAR29 = '0.0155745269463051';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.819880926935971'; $VAR2 = '0.0729512634569128'; $VAR3 = '0.107167809607116';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.568427357566022'; $VAR3 = 26; $VAR4 = '0.431572642433978';
Author Z-Score-Based P-Values
$VAR1 = '0.127635123348666'; $VAR2 = '0.000161005483443711'; $VAR3 = '0.0325762869441846';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0249236335642817'; $VAR2 = '0.000195949126252223'; $VAR3 = '0.0397640629310382'; $VAR4 = '0.0442602718403091'; $VAR5 = '0.021287838870501'; $VAR6 = '1.24345470755688e-35'; $VAR7 = '1.30142246256675e-07'; $VAR8 = '0'; $VAR9 = '1.08897174676258e-232'; $VAR10 = '9.4638749992208e-91'; $VAR11 = '0.00333314545480604'; $VAR12 = '4.45327558615917e-25'; $VAR13 = '0.00328320445284432'; $VAR14 = '0.00185571161600504'; $VAR15 = '0.0138703432634595'; $VAR16 = '0.00555228719234714'; $VAR17 = '0.0357386810494259'; $VAR18 = '2.36037109634694e-06'; $VAR19 = '0.000172656833885411'; $VAR20 = '2.41367325438706e-10'; $VAR21 = '2.80235898635616e-09'; $VAR22 = '9.4003667791662e-06'; $VAR23 = '0.0347238835919638'; $VAR24 = '2.25716876895229e-11'; $VAR25 = '0.0110761997067075'; $VAR26 = '0.0401505144431028'; $VAR27 = '7.54931737203513e-10'; $VAR28 = '0.0134465916862291'; $VAR29 = '0.00658066002496649';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.795867061868706'; $VAR2 = '0.00100394748476135'; $VAR3 = '0.203128990646532';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.742516244884564'; $VAR3 = 4; $VAR4 = '0.257483755115436';
Author Z-Score-Based P-Values
$VAR1 = '0.13738137999186'; $VAR2 = '0.00530013818383036'; $VAR3 = '0.0437171656181973';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0149616848741633'; $VAR2 = '0.00129207669596575'; $VAR3 = '0.0655531990569553'; $VAR4 = '0.0780435496146124'; $VAR5 = '0.00398209907694098'; $VAR6 = '1.81544686730898e-08'; $VAR7 = '2.63510503015552e-06'; $VAR8 = '4.46067998569299e-14'; $VAR9 = '2.70382395087962e-194'; $VAR10 = '1.55025254228169e-28'; $VAR11 = '0.000901275889851466'; $VAR12 = '4.25800570432781e-19'; $VAR13 = '0.000395758026310977'; $VAR14 = '0.00205049563824668'; $VAR15 = '0.00786214433048355'; $VAR16 = '0.00764262797208844'; $VAR17 = '0.0271316237041956'; $VAR18 = '2.7102017150026e-06'; $VAR19 = '0.000797181870815189'; $VAR20 = '4.47802000788539e-06'; $VAR21 = '5.30174657255771e-07'; $VAR22 = '0.000135749404947173'; $VAR23 = '0.0140624866737551'; $VAR24 = '0.00382965516715977'; $VAR25 = '0.0253111330350242'; $VAR26 = '0.0970014317859946'; $VAR27 = '1.3192312142553e-05'; $VAR28 = '0.0387486871259045'; $VAR29 = '0.0418227102338343';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.737029775080231'; $VAR2 = '0.0284344185052886'; $VAR3 = '0.234535806414481';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.58614101840398'; $VAR3 = 26; $VAR4 = '0.41385898159602';
Author Z-Score-Based P-Values
$VAR1 = '0.136370802057711'; $VAR2 = '0.00159857833163258'; $VAR3 = '0.0172956949153583';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.00568610916986102'; $VAR2 = '0.00456936695187693'; $VAR3 = '0.0636686809739386'; $VAR4 = '0.0680755406253694'; $VAR5 = '0.00514832785670642'; $VAR6 = '4.60793415446126e-11'; $VAR7 = '6.91315501037634e-08'; $VAR8 = '2.14298109929115e-08'; $VAR9 = '1.60155047762868e-249'; $VAR10 = '3.08146853487366e-29'; $VAR11 = '0.0082120240306622'; $VAR12 = '2.50211998533869e-16'; $VAR13 = '0.000236921602727938'; $VAR14 = '0.00826720127873251'; $VAR15 = '0.010133424632304'; $VAR16 = '0.0189382765303874'; $VAR17 = '0.0526026982256684'; $VAR18 = '2.77483432444593e-10'; $VAR19 = '0.000226355763090211'; $VAR20 = '1.16122599317272e-06'; $VAR21 = '9.24903611121384e-07'; $VAR22 = '0.000301723330503152'; $VAR23 = '0.0160206628835168'; $VAR24 = '0.00164787006584991'; $VAR25 = '0.047720212632697'; $VAR26 = '0.0600367493074169'; $VAR27 = '4.18864905077825e-06'; $VAR28 = '0.0329770370671062'; $VAR29 = '0.00739714314530839';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.878309573418803'; $VAR2 = '0.0102958010904605'; $VAR3 = '0.111394625490737';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.667024903786634'; $VAR3 = 4; $VAR4 = '0.332975096213366';
Author Z-Score-Based P-Values
$VAR1 = '0.14278106513849'; $VAR2 = '0.00997493711260808'; $VAR3 = '0.0761397408138361';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0211599582692338'; $VAR2 = '0.00363064656281264'; $VAR3 = '0.0367122613590212'; $VAR4 = '0.0451035143944168'; $VAR5 = '0.00407073643440096'; $VAR6 = '8.13582348302604e-12'; $VAR7 = '1.30876062242339e-08'; $VAR8 = '2.93545026254554e-17'; $VAR9 = '1.55120811858387e-249'; $VAR10 = '9.76528916397391e-236'; $VAR11 = '0.00022354346101783'; $VAR12 = '1.01254663831992e-20'; $VAR13 = '0.000970427679693843'; $VAR14 = '0.0193643941913745'; $VAR15 = '0.011113006859313'; $VAR16 = '0.0304550530958849'; $VAR17 = '0.0926016269798557'; $VAR18 = '3.63123856023538e-06'; $VAR19 = '0.00225693366535087'; $VAR20 = '0.000788555573142484'; $VAR21 = '0.000167302481797237'; $VAR22 = '0.00659841150935002'; $VAR23 = '0.0353272912587754'; $VAR24 = '0.00450306594057594'; $VAR25 = '0.0210389680189147'; $VAR26 = '0.0492579294174438'; $VAR27 = '0.0111052701144541'; $VAR28 = '0.0355933040971247'; $VAR29 = '0.0597516361165316';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.623782090600022'; $VAR2 = '0.0435785173592255'; $VAR3 = '0.332639392040753';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.606591180742816'; $VAR3 = 17; $VAR4 = '0.393408819257184';
Author Z-Score-Based P-Values
$VAR1 = '0.120471364806243'; $VAR2 = '0.0162388685617554'; $VAR3 = '0.0459337033815459';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0195776421949735'; $VAR2 = '0.00508212995090966'; $VAR3 = '0.0452433495816131'; $VAR4 = '0.0419806074102327'; $VAR5 = '0.00197943639376425'; $VAR6 = '1.31162890177067e-11'; $VAR7 = '5.15478494565572e-08'; $VAR8 = '1.64427061191786e-12'; $VAR9 = '1.99419046393481e-278'; $VAR10 = '9.09233604201113e-235'; $VAR11 = '6.35596380937309e-06'; $VAR12 = '2.36584286030872e-20'; $VAR13 = '2.17037662681308e-05'; $VAR14 = '0.00374974857661464'; $VAR15 = '0.00569289008431'; $VAR16 = '0.0239483837880326'; $VAR17 = '0.046516541569381'; $VAR18 = '8.76618186095479e-05'; $VAR19 = '0.00290968599584928'; $VAR20 = '0.00122890914156351'; $VAR21 = '0.000310871408621188'; $VAR22 = '0.0118792329789819'; $VAR23 = '0.0181705324670237'; $VAR24 = '0.000836237854485852'; $VAR25 = '0.014470316005342'; $VAR26 = '0.0521271403191852'; $VAR27 = '0.0103171454274442'; $VAR28 = '0.0311503162895643'; $VAR29 = '0.0189896369112289';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.659596847014105'; $VAR2 = '0.0889099788952942'; $VAR3 = '0.251493174090601';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.697986142572301'; $VAR3 = 26; $VAR4 = '0.3020138574277';
Author Z-Score-Based P-Values
$VAR1 = '0.0681560263593454'; $VAR2 = '0.00567815620741305'; $VAR3 = '0.0818869497635298';
Good match. Z-Score-Based P-Value > 0.05.
Control Z-Score-Based P-Values
$VAR1 = '0.0369453019167157'; $VAR2 = '0.00667417909576646'; $VAR3 = '0.0408707884218824'; $VAR4 = '0.0388687361545007'; $VAR5 = '0.0061412858488877'; $VAR6 = '1.81249692477716e-13'; $VAR7 = '8.88366382355043e-13'; $VAR8 = '1.45731151767119e-23'; $VAR9 = '0'; $VAR10 = '6.43779705196076e-74'; $VAR11 = '0.00264709903943586'; $VAR12 = '4.73609442383191e-20'; $VAR13 = '0.00204116499497372'; $VAR14 = '0.0220899232232348'; $VAR15 = '0.0206425169940387'; $VAR16 = '0.0370990687208815'; $VAR17 = '0.0657884676089261'; $VAR18 = '0.0236326485453446'; $VAR19 = '0.0129272807154352'; $VAR20 = '0.00300271962117876'; $VAR21 = '0.0021221685121358'; $VAR22 = '0.0195135696971412'; $VAR23 = '0.0809185232532458'; $VAR24 = '8.01610225955405e-13'; $VAR25 = '0.00069909167914679'; $VAR26 = '0.012529095139316'; $VAR27 = '0.0132373345674838'; $VAR28 = '0.00854334996233293'; $VAR29 = '0.0115132573365989';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.437680007455795'; $VAR2 = '0.036463620078035'; $VAR3 = '0.52585637246617';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.502974182907795'; $VAR3 = 23; $VAR4 = '0.497025817092205';
Author Z-Score-Based P-Values
$VAR1 = '0.122360514871706'; $VAR2 = '0.0020295026025486'; $VAR3 = '0.0423668554353428';
Excellent match. Z-Score-Based P-Value > 0.10.
Control Z-Score-Based P-Values
$VAR1 = '0.0144049783845335'; $VAR2 = '0.0145038631784281'; $VAR3 = '0.0687224792012786'; $VAR4 = '0.108417694522221'; $VAR5 = '0.0542926979914485'; $VAR6 = '4.54873449688004e-11'; $VAR7 = '9.15805274686801e-08'; $VAR8 = '0'; $VAR9 = '4.69116018964686e-263'; $VAR10 = '2.33332083972019e-77'; $VAR11 = '0.0246851172389869'; $VAR12 = '3.62961477959803e-14'; $VAR13 = '0.000245801839435087'; $VAR14 = '0.0101187054318321'; $VAR15 = '0.0147920493197497'; $VAR16 = '0.0158339553964157'; $VAR17 = '0.0419279804119123'; $VAR18 = '0.000280579993972628'; $VAR19 = '0.00338974876798934'; $VAR20 = '5.49632491709367e-07'; $VAR21 = '2.00132515228599e-05'; $VAR22 = '0.000478244026570665'; $VAR23 = '0.0275792780796866'; $VAR24 = '9.65289021430619e-06'; $VAR25 = '0.0060473892411165'; $VAR26 = '0.0190793313089856'; $VAR27 = '3.18806228752215e-05'; $VAR28 = '0.0212429758836958'; $VAR29 = '0.0206027557417192';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.733765947614288'; $VAR2 = '0.0121704285234998'; $VAR3 = '0.254063623862212';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.53020826876615'; $VAR3 = 4; $VAR4 = '0.46979173123385';
testsize: 2663
$VAR1 = 59; $VAR2 = 29; $VAR3 = 64; $VAR4 = 147; $VAR5 = 8; $VAR6 = 44; $VAR7 = 9; $VAR8 = 19; $VAR9 = 22; $VAR10 = 30; $VAR11 = 48; $VAR12 = 26; $VAR13 = 16; $VAR14 = 5; $VAR15 = 10; $VAR16 = 10; $VAR17 = 9; $VAR18 = 6; $VAR19 = 10; $VAR20 = 6; $VAR21 = 18; $VAR22 = 20;
22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];
Author Z-Score-Based P-Values
$VAR1 = '0.0851802438581617'; $VAR2 = '0.0724749834074447'; $VAR3 = '0.064286883957332';
Good match. Z-Score-Based P-Value > 0.05.
Control Z-Score-Based P-Values
$VAR1 = '0.00190437533607135'; $VAR2 = '0.0134963811649367'; $VAR3 = '0.141273334998977'; $VAR4 = '0.124951326899165'; $VAR5 = '0.0518220257168887'; $VAR6 = '2.16760803715612e-06'; $VAR7 = '0.000296736155878467'; $VAR8 = '6.929923557776e-12'; $VAR9 = '3.79213525315146e-67'; $VAR10 = '2.2577358826784e-16'; $VAR11 = '0.00273097840803051'; $VAR12 = '7.42388525889789e-09'; $VAR13 = '0.00435259762804016'; $VAR14 = '0.00143267823333169'; $VAR15 = '0.00337363803985972'; $VAR16 = '0.00828495704831723'; $VAR17 = '0.010618325608902'; $VAR18 = '5.98973976614139e-07'; $VAR19 = '0.000594576185258456'; $VAR20 = '4.96432404140559e-09'; $VAR21 = '7.18452132102276e-10'; $VAR22 = '3.01670111804679e-05'; $VAR23 = '0.0244209185087774'; $VAR24 = '6.0996662018508e-05'; $VAR25 = '0.0179900750931756'; $VAR26 = '0.14545087264223'; $VAR27 = '2.10064907187007e-08'; $VAR28 = '0.119497354155087'; $VAR29 = '0.00551171200172479';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.383794870602989'; $VAR2 = '0.32654904023439'; $VAR3 = '0.289656089162622';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.369335435524447'; $VAR3 = 26; $VAR4 = '0.630664564475553';
Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0851 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0851 Test, Z-Score-Based Method
0.3359375
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.748538011695906
Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0851 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1
Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0851 Test, Z-Score-Based Method
0.833333333333333
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.545454545454545
This seemed to be a handy metric of the validity of a result, so it's been baked into the printed results.Peter Kirby wrote: If using a 'z-scored p-value < 0.1' test, only 10 of 32 candidates are excluded.
If using a 'z-scored p-value < 0.05' test, only 3 of 32 candidates are excluded.
testsize: 2663
$VAR1 = 59; $VAR2 = 29; $VAR3 = 64; $VAR4 = 147; $VAR5 = 8; $VAR6 = 44; $VAR7 = 9; $VAR8 = 19; $VAR9 = 22; $VAR10 = 30; $VAR11 = 48; $VAR12 = 26; $VAR13 = 16; $VAR14 = 5; $VAR15 = 10; $VAR16 = 10; $VAR17 = 9; $VAR18 = 6; $VAR19 = 10; $VAR20 = 6; $VAR21 = 18; $VAR22 = 20;
22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];
Author Z-Score-Based P-Values
$VAR1 = '0.0850371937529633'; $VAR2 = '0.0725428286743953'; $VAR3 = '0.0645305982464296';
Decent compatibility. Z-Score-Based P-Value > 0.05.
Poor indicator. 22.5% others with P-Value > 0.05.
Control Z-Score-Based P-Values
$VAR1 = '0.00188696923841321'; $VAR2 = '0.0134054452934796'; $VAR3 = '0.14121502037573'; $VAR4 = '0.125519981945472'; $VAR5 = '0.0521983563840763'; $VAR6 = '2.1707630208328e-06'; $VAR7 = '0.000296715186260485'; $VAR8 = '6.93442929575849e-12'; $VAR9 = '1.7299079994794e-67'; $VAR10 = '7.47851133323473e-17'; $VAR11 = '0.002791748346296'; $VAR12 = '9.34882392453667e-09'; $VAR13 = '0.00430737734281189'; $VAR14 = '0.00143248134317908'; $VAR15 = '0.00349081485947745'; $VAR16 = '0.0081767518985651'; $VAR17 = '0.0105903941027185'; $VAR18 = '5.98856413343923e-07'; $VAR19 = '0.000594577047668175'; $VAR20 = '4.96428289372844e-09'; $VAR21 = '7.18444719382476e-10'; $VAR22 = '3.01661467556279e-05'; $VAR23 = '0.0244207670023187'; $VAR24 = '6.09948007155562e-05'; $VAR25 = '0.017990161932696'; $VAR26 = '0.14545117735424'; $VAR27 = '2.10058996891061e-08'; $VAR28 = '0.119497447614848'; $VAR29 = '0.00551173549315115';
Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.382859646670641'; $VAR2 = '0.326606753222028'; $VAR3 = '0.290533600107331';
Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.368943532137729'; $VAR3 = 26; $VAR4 = '0.631056467862271';
Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.085 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.085 Test, Z-Score-Based Method
0.33984375
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.746355685131195
Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.085 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1
Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.085 Test, Z-Score-Based Method
0.833333333333333
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.545454545454545
These were the aggregated P-Values for each author/control, compared against the test sample. They are 'aggregated' in the sense that they come from a weighted average, calculated over all the 20 words whose frequencies are measured. Each of the twenty individual "P-values" (the likelihood of the observed frequency being that far off the mean) go into the weighted average, trying to gauge how likely it is that the author/control would have produced the sample.Tenorikuma wrote:I confess to not knowing what most of the numbers mean. But if Clement is the top match out of all author candidates and controls, surely that itself is somewhat remarkable. Either that, or a forger is purposely trying to fool stylometric analysis by copying sentence construction patterns from genuine works by Clement. Or have I misunderstood?
You could put them in two categories if you like (those with scores close to or higher than 'Clement', and those without):Author Chi-Square-Based P-Values
$VAR1 = '0.897126717178744'; $VAR2 = '0.876686010922532'; $VAR3 = '0.766954128799045';
Control Chi-Square-Based P-Values
$VAR1 = '0.137898770544387'; $VAR2 = '0.263214501782374'; $VAR3 = '0.97251600690767'; $VAR4 = '0.996383635782013'; $VAR5 = '0.995727137880758'; $VAR6 = '0.000948092883388932'; $VAR7 = '0.253210360195565'; $VAR8 = '0.00852822453421988'; $VAR9 = '0.65938916375342'; $VAR10 = 0; $VAR11 = '0.346606811740825'; $VAR12 = '1.0011159413525e-12'; $VAR13 = '0.00377297557020349'; $VAR14 = '0.169854249175826'; $VAR15 = '0.599467656898274'; $VAR16 = '0.493172636244664'; $VAR17 = '0.912577608896469'; $VAR18 = '0.277004254454816'; $VAR19 = '0.00103826061119019'; $VAR20 = '0.149481145224522'; $VAR21 = '0.000251868655303691'; $VAR22 = '0.851018068030414'; $VAR23 = '0.697616764950275'; $VAR24 = '0.442629632622023'; $VAR25 = '0.993407920946543'; $VAR26 = '0.98246524429608'; $VAR27 = '0.118313132250566'; $VAR28 = '0.998364840186754'; $VAR29 = '0.8885746060188';
Here are the words (at least, this is a 22-word list, used with the above 22-word list of means and standard deviations):$VAR1 = #1 [ [ '10.235632183908', '4.19313826487864' ], #2 [ '5.66091954022988', '3.41312060406515' ], #3 [ '16.2528735632184', '6.95175226534479' ], #4 [ '39.6551724137931', '7.76053616201855' ], #5 [ '5.17816091954023', '3.71040553867919' ], #6 [ '22.1034482758621', '5.65285907268176' ], #7 [ '6.59770114942529', '3.06053774147782' ], #8 [ '4.88505747126437', '2.36801137460534' ], #9 [ '8.49425287356322', '3.25672977227436' ], #10 [ '5.53448275862069', '3.10106869180802' ], #11 [ '6.14942528735632', '3.7463506707016' ], #12 [ '3.13218390804598', '2.56855405689453' ], #13 [ '4.62068965517241', '3.64751964002605' ], #14 [ '3.9367816091954', '2.4521918388198' ], #15 [ '2.94827586206897', '1.8107826509434' ], #16 [ '0.67816091954023', '0.909645034641222' ], #17 [ '1.36206896551724', '1.45465889506471' ], #18 [ '1.08045977011494', '1.37897505503346' ], #19 [ '2.56896551724138', '2.40051768098924' ], #20 [ '1.37931034482759', '1.29757846360185' ], #21 [ '3.26436781609195', '2.41384783736521' ], #22 [ '3.4367816091954', '2.18774617360459' ] ];
And here were the observed frequencies for the test sample:$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];
Right off the bat, my program will discard 10 of these words entirely when calculating a Z-score for Clement, because they have a mean number of occurences below 4... this is just a basic prevention against counting data when there is nothing really expected to be there to count.testsize: 749
$VAR1 = 14; $VAR2 = 3; $VAR3 = 15; $VAR4 = 45; $VAR5 = 1; $VAR6 = 15; $VAR7 = 3; $VAR8 = 4; $VAR9 = 9; $VAR10 = 0; $VAR11 = 5; $VAR12 = 7; $VAR13 = 7; $VAR14 = 0; $VAR15 = 3; $VAR16 = 1; $VAR17 = 0; $VAR18 = 2; $VAR19 = 3; $VAR20 = 1; $VAR21 = 4; $VAR22 = 2;