Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications
Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing o...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Xiao [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2022 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© The Psychonomic Society, Inc. 2022 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Behavior research methods, instruments & computers - Austin, Tex. : Psychonomic Society Publ., 1984, 55(2022), 3 vom: 17. Mai, Seite 1108-1120 |
|---|---|
| Übergeordnetes Werk: |
volume:55 ; year:2022 ; number:3 ; day:17 ; month:05 ; pages:1108-1120 |
| Links: |
|---|
| DOI / URN: |
10.3758/s13428-022-01860-1 |
|---|
| Katalog-ID: |
SPR050168592 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | SPR050168592 | ||
| 003 | DE-627 | ||
| 005 | 20230726104051.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230425s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.3758/s13428-022-01860-1 |2 doi | |
| 035 | |a (DE-627)SPR050168592 | ||
| 035 | |a (SPR)s13428-022-01860-1-e | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Liu, Xiao |e verfasserin |0 (orcid)0000-0002-4526-3221 |4 aut | |
| 245 | 1 | 0 | |a Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a © The Psychonomic Society, Inc. 2022 | ||
| 520 | |a Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. | ||
| 650 | 4 | |a Bayes factor |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Mediation analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Bayesian hypothesis testing |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Zhang, Zhiyong |4 aut | |
| 700 | 1 | |a Wang, Lijuan |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Behavior research methods, instruments & computers |d Austin, Tex. : Psychonomic Society Publ., 1984 |g 55(2022), 3 vom: 17. Mai, Seite 1108-1120 |w (DE-627)32998067X |w (DE-600)2048669-8 |x 1532-5970 |7 nnns |
| 773 | 1 | 8 | |g volume:55 |g year:2022 |g number:3 |g day:17 |g month:05 |g pages:1108-1120 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.3758/s13428-022-01860-1 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_SPRINGER | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_32 | ||
| 912 | |a GBV_ILN_39 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_60 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_74 | ||
| 912 | |a GBV_ILN_90 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_100 | ||
| 912 | |a GBV_ILN_101 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_120 | ||
| 912 | |a GBV_ILN_138 | ||
| 912 | |a GBV_ILN_152 | ||
| 912 | |a GBV_ILN_161 | ||
| 912 | |a GBV_ILN_171 | ||
| 912 | |a GBV_ILN_187 | ||
| 912 | |a GBV_ILN_224 | ||
| 912 | |a GBV_ILN_250 | ||
| 912 | |a GBV_ILN_281 | ||
| 912 | |a GBV_ILN_285 | ||
| 912 | |a GBV_ILN_293 | ||
| 912 | |a GBV_ILN_370 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_702 | ||
| 912 | |a GBV_ILN_2014 | ||
| 951 | |a AR | ||
| 952 | |d 55 |j 2022 |e 3 |b 17 |c 05 |h 1108-1120 | ||
| author_variant |
x l xl z z zz l w lw |
|---|---|
| matchkey_str |
article:15325970:2022----::aeinyohssetnomdainehdadhipcopi |
| hierarchy_sort_str |
2022 |
| publishDate |
2022 |
| allfields |
10.3758/s13428-022-01860-1 doi (DE-627)SPR050168592 (SPR)s13428-022-01860-1-e DE-627 ger DE-627 rakwb eng Liu, Xiao verfasserin (orcid)0000-0002-4526-3221 aut Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2022 Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. Bayes factor (dpeaa)DE-He213 Mediation analysis (dpeaa)DE-He213 Bayesian hypothesis testing (dpeaa)DE-He213 Zhang, Zhiyong aut Wang, Lijuan aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 55(2022), 3 vom: 17. Mai, Seite 1108-1120 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:55 year:2022 number:3 day:17 month:05 pages:1108-1120 https://dx.doi.org/10.3758/s13428-022-01860-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 55 2022 3 17 05 1108-1120 |
| spelling |
10.3758/s13428-022-01860-1 doi (DE-627)SPR050168592 (SPR)s13428-022-01860-1-e DE-627 ger DE-627 rakwb eng Liu, Xiao verfasserin (orcid)0000-0002-4526-3221 aut Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2022 Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. Bayes factor (dpeaa)DE-He213 Mediation analysis (dpeaa)DE-He213 Bayesian hypothesis testing (dpeaa)DE-He213 Zhang, Zhiyong aut Wang, Lijuan aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 55(2022), 3 vom: 17. Mai, Seite 1108-1120 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:55 year:2022 number:3 day:17 month:05 pages:1108-1120 https://dx.doi.org/10.3758/s13428-022-01860-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 55 2022 3 17 05 1108-1120 |
| allfields_unstemmed |
10.3758/s13428-022-01860-1 doi (DE-627)SPR050168592 (SPR)s13428-022-01860-1-e DE-627 ger DE-627 rakwb eng Liu, Xiao verfasserin (orcid)0000-0002-4526-3221 aut Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2022 Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. Bayes factor (dpeaa)DE-He213 Mediation analysis (dpeaa)DE-He213 Bayesian hypothesis testing (dpeaa)DE-He213 Zhang, Zhiyong aut Wang, Lijuan aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 55(2022), 3 vom: 17. Mai, Seite 1108-1120 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:55 year:2022 number:3 day:17 month:05 pages:1108-1120 https://dx.doi.org/10.3758/s13428-022-01860-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 55 2022 3 17 05 1108-1120 |
| allfieldsGer |
10.3758/s13428-022-01860-1 doi (DE-627)SPR050168592 (SPR)s13428-022-01860-1-e DE-627 ger DE-627 rakwb eng Liu, Xiao verfasserin (orcid)0000-0002-4526-3221 aut Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2022 Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. Bayes factor (dpeaa)DE-He213 Mediation analysis (dpeaa)DE-He213 Bayesian hypothesis testing (dpeaa)DE-He213 Zhang, Zhiyong aut Wang, Lijuan aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 55(2022), 3 vom: 17. Mai, Seite 1108-1120 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:55 year:2022 number:3 day:17 month:05 pages:1108-1120 https://dx.doi.org/10.3758/s13428-022-01860-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 55 2022 3 17 05 1108-1120 |
| allfieldsSound |
10.3758/s13428-022-01860-1 doi (DE-627)SPR050168592 (SPR)s13428-022-01860-1-e DE-627 ger DE-627 rakwb eng Liu, Xiao verfasserin (orcid)0000-0002-4526-3221 aut Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2022 Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. Bayes factor (dpeaa)DE-He213 Mediation analysis (dpeaa)DE-He213 Bayesian hypothesis testing (dpeaa)DE-He213 Zhang, Zhiyong aut Wang, Lijuan aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 55(2022), 3 vom: 17. Mai, Seite 1108-1120 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:55 year:2022 number:3 day:17 month:05 pages:1108-1120 https://dx.doi.org/10.3758/s13428-022-01860-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 55 2022 3 17 05 1108-1120 |
| language |
English |
| source |
Enthalten in Behavior research methods, instruments & computers 55(2022), 3 vom: 17. Mai, Seite 1108-1120 volume:55 year:2022 number:3 day:17 month:05 pages:1108-1120 |
| sourceStr |
Enthalten in Behavior research methods, instruments & computers 55(2022), 3 vom: 17. Mai, Seite 1108-1120 volume:55 year:2022 number:3 day:17 month:05 pages:1108-1120 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Bayes factor Mediation analysis Bayesian hypothesis testing |
| isfreeaccess_bool |
false |
| container_title |
Behavior research methods, instruments & computers |
| authorswithroles_txt_mv |
Liu, Xiao @@aut@@ Zhang, Zhiyong @@aut@@ Wang, Lijuan @@aut@@ |
| publishDateDaySort_date |
2022-05-17T00:00:00Z |
| hierarchy_top_id |
32998067X |
| id |
SPR050168592 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR050168592</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230726104051.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230425s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3758/s13428-022-01860-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR050168592</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13428-022-01860-1-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Liu, Xiao</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-4526-3221</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Psychonomic Society, Inc. 2022</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayes factor</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mediation analysis</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayesian hypothesis testing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Zhiyong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Lijuan</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Behavior research methods, instruments & computers</subfield><subfield code="d">Austin, Tex. : Psychonomic Society Publ., 1984</subfield><subfield code="g">55(2022), 3 vom: 17. Mai, Seite 1108-1120</subfield><subfield code="w">(DE-627)32998067X</subfield><subfield code="w">(DE-600)2048669-8</subfield><subfield code="x">1532-5970</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:55</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:3</subfield><subfield code="g">day:17</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:1108-1120</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.3758/s13428-022-01860-1</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_101</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">55</subfield><subfield code="j">2022</subfield><subfield code="e">3</subfield><subfield code="b">17</subfield><subfield code="c">05</subfield><subfield code="h">1108-1120</subfield></datafield></record></collection>
|
| author |
Liu, Xiao |
| spellingShingle |
Liu, Xiao misc Bayes factor misc Mediation analysis misc Bayesian hypothesis testing Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications |
| authorStr |
Liu, Xiao |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)32998067X |
| format |
electronic Article |
| delete_txt_mv |
keep |
| author_role |
aut aut aut |
| collection |
springer |
| remote_str |
true |
| illustrated |
Not Illustrated |
| issn |
1532-5970 |
| topic_title |
Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications Bayes factor (dpeaa)DE-He213 Mediation analysis (dpeaa)DE-He213 Bayesian hypothesis testing (dpeaa)DE-He213 |
| topic |
misc Bayes factor misc Mediation analysis misc Bayesian hypothesis testing |
| topic_unstemmed |
misc Bayes factor misc Mediation analysis misc Bayesian hypothesis testing |
| topic_browse |
misc Bayes factor misc Mediation analysis misc Bayesian hypothesis testing |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Behavior research methods, instruments & computers |
| hierarchy_parent_id |
32998067X |
| hierarchy_top_title |
Behavior research methods, instruments & computers |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)32998067X (DE-600)2048669-8 |
| title |
Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications |
| ctrlnum |
(DE-627)SPR050168592 (SPR)s13428-022-01860-1-e |
| title_full |
Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications |
| author_sort |
Liu, Xiao |
| journal |
Behavior research methods, instruments & computers |
| journalStr |
Behavior research methods, instruments & computers |
| lang_code |
eng |
| isOA_bool |
false |
| recordtype |
marc |
| publishDateSort |
2022 |
| contenttype_str_mv |
txt |
| container_start_page |
1108 |
| author_browse |
Liu, Xiao Zhang, Zhiyong Wang, Lijuan |
| container_volume |
55 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Liu, Xiao |
| doi_str_mv |
10.3758/s13428-022-01860-1 |
| normlink |
(ORCID)0000-0002-4526-3221 |
| normlink_prefix_str_mv |
(orcid)0000-0002-4526-3221 |
| title_sort |
bayesian hypothesis testing of mediation: methods and the impact of prior odds specifications |
| title_auth |
Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications |
| abstract |
Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. © The Psychonomic Society, Inc. 2022 |
| abstractGer |
Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. © The Psychonomic Society, Inc. 2022 |
| abstract_unstemmed |
Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation. © The Psychonomic Society, Inc. 2022 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 |
| container_issue |
3 |
| title_short |
Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications |
| url |
https://dx.doi.org/10.3758/s13428-022-01860-1 |
| remote_bool |
true |
| author2 |
Zhang, Zhiyong Wang, Lijuan |
| author2Str |
Zhang, Zhiyong Wang, Lijuan |
| ppnlink |
32998067X |
| mediatype_str_mv |
c |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.3758/s13428-022-01860-1 |
| up_date |
2024-07-03T13:49:23.778Z |
| _version_ |
1803565991232274432 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR050168592</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230726104051.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230425s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3758/s13428-022-01860-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR050168592</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13428-022-01860-1-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Liu, Xiao</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-4526-3221</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Bayesian hypothesis testing of mediation: Methods and the impact of prior odds specifications</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Psychonomic Society, Inc. 2022</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes factor for a single path is readily available, how to integrate the Bayes factors of two paths (from input to mediator and from mediator to outcome) while incorporating prior beliefs on the two paths and/or mediation is under-studied. In the current study, we propose a general approach to Bayesian hypothesis testing of mediation. The proposed approach allows researchers to specify prior odds based on the substantive research context and can be used in mediation modeling with latent variables. The impact of prior odds specifications on Bayesian hypothesis test of mediation is demonstrated via both real and hypothetical data examples. Both R functions and a user-friendly R web app are provided for the implementation of the proposed approach. Our study can add to researchers’ toolbox of mediation analysis and raise researchers’ awareness of the importance of prior odds specifications in Bayesian hypothesis testing of mediation.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayes factor</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mediation analysis</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayesian hypothesis testing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Zhiyong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Lijuan</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Behavior research methods, instruments & computers</subfield><subfield code="d">Austin, Tex. : Psychonomic Society Publ., 1984</subfield><subfield code="g">55(2022), 3 vom: 17. Mai, Seite 1108-1120</subfield><subfield code="w">(DE-627)32998067X</subfield><subfield code="w">(DE-600)2048669-8</subfield><subfield code="x">1532-5970</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:55</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:3</subfield><subfield code="g">day:17</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:1108-1120</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.3758/s13428-022-01860-1</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_101</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">55</subfield><subfield code="j">2022</subfield><subfield code="e">3</subfield><subfield code="b">17</subfield><subfield code="c">05</subfield><subfield code="h">1108-1120</subfield></datafield></record></collection>
|
| score |
7.3971796 |