Overview of Data Sets Included in the Meta-Analysis
MPT Reanalysis Project (code and text current document: Henrik Singmann)
Results from: 2021-06-01
Models
The results include 9 different models (some of which with additional submodels):
2htsm: 2-high threshold source memory modelc2ht: confidence-rating 2-high threshold memory modelpc: pair-clustering modelpd: process-dissociationpm: prospective memory modelhb: hindsight-bias modelrm: r-modelreal: real model (IAT)quad: quad model (IAT)
Participants and Studies
The following table gives an overview of the number of conditions (n_within_between is the number of conditions that each provide at least one parameter per model that otherwise would not be unique given the base-model equations, this includes both within-subjects and between-conditions; n_between is the number of between-subjects conditions), number of participants (par), and number of data sets (n_study). The final table shows the overall results.
## # A tibble: 9 x 5
## model par n_within_between n_between n_study
## <fct> <int> <int> <int> <int>
## 1 2htsm 2668 144 88 35
## 2 c2ht 850 15 15 15
## 3 pc 551 82 15 9
## 4 pd 679 33 16 10
## 5 pm 1323 36 30 14
## 6 hb 943 26 25 9
## 7 rm 2680 66 66 42
## 8 real 753 21 21 9
## 9 quad 3509 29 29 21## # A tibble: 1 x 4
## par n_within_between n_between n_study
## <int> <int> <int> <int>
## 1 13956 452 305 164We can also make this table by submodel.
## # A tibble: 13 x 5
## model2 par n_within_between n_between n_study
## <fct> <int> <int> <int> <int>
## 1 2htsm_4 1148 104 70 19
## 2 2htsm_5d 1012 33 14 12
## 3 2htsm_6e 508 7 4 4
## 4 c2ht6 459 12 12 12
## 5 c2ht8 391 3 3 3
## 6 pc 551 82 15 9
## 7 pd_s 437 21 13 7
## 8 pd_e 242 12 3 3
## 9 pm 1323 36 30 14
## 10 hb 943 26 25 9
## 11 rm 2680 66 66 42
## 12 real 753 21 21 9
## 13 quad 3509 29 29 21## # A tibble: 1 x 4
## par n_within_between n_between n_study
## <int> <int> <int> <int>
## 1 13956 452 305 164Number of Parameter Estimates
We can also get an overview of the number of (core) parameter estimates per model:
## # A tibble: 9 x 2
## model n
## <fct> <int>
## 1 2htsm 623
## 2 c2ht 45
## 3 pc 246
## 4 pd 62
## 5 pm 144
## 6 hb 103
## 7 rm 264
## 8 real 147
## 9 quad 145Overall this provides the following number of estimates:
## # A tibble: 1 x 1
## n
## <int>
## 1 1779If we include all parameters (i.e., core and non-core) we get the following table:
## # A tibble: 9 x 2
## model n
## <fct> <int>
## 1 2htsm 623
## 2 c2ht 159
## 3 pc 246
## 4 pd 62
## 5 pm 144
## 6 hb 331
## 7 rm 264
## 8 real 210
## 9 quad 145Methods
The following table gives the proportion of data sets for which a given method (in columns) produced usable results (i.e., also considering our convergence criteria). This first table is separated by models.
## # A tibble: 9 x 11
## model `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2htsm 1 1 1 1 1 0.971 0 1 0.943 0.914
## 2 c2ht 1 1 1 1 1 0.8 0 0.933 1 1
## 3 pc 1 1 1 1 1 1 0 1 1 1
## 4 pd 1 1 1 1 1 1 1 1 1 0.9
## 5 pm 1 1 1 1 1 1 0 1 1 0.929
## 6 hb 1 1 1 1 0.667 1 0 0.889 0.444 0.778
## 7 rm 1 1 1 1 1 1 0.952 1 1 1
## 8 real 1 1 1 1 1 0.778 0 1 1 1
## 9 quad 1 1 1 1 1 1 0 1 0.952 0.952One thing that is clear is that the latent class approach (LC PP) is missing in the vast majority of cases.
We can also look at this across all models.
## # A tibble: 1 x 10
## `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 1 1 0.982 0.963 0.305 0.988 0.951 0.951Methods per Data Set
The following tables, which are separated by model, provide an overview of whether each method is usable (TRUE), misses our convergence criteria (FALSE), or is missing (NA).
## # A tibble: 35 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 2htsm A2013 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 2 2htsm Bell et al. (2015) Ex1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 3 2htsm Bell et al. (2015) Ex2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 4 2htsm Bell et al. (2015) Ex3 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 5 2htsm Bell et al. (2015) Ex4 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 6 2htsm BG2008 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE FALSE TRUE
## 7 2htsm BK2011_E1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 8 2htsm BK2011_E2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE FALSE TRUE
## 9 2htsm DS2000_E1 TRUE TRUE TRUE TRUE TRUE FALSE NA TRUE TRUE TRUE
## 10 2htsm DS2000_E3 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 11 2htsm DS2000_E4 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE FALSE
## 12 2htsm Giang et al. (2012) TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 13 2htsm K2012_E1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 14 2htsm K2016_E1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 15 2htsm K2016_E2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 16 2htsm KB2018 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 17 2htsm KM2000_E3 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 18 2htsm KM2000_E4 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE FALSE
## 19 2htsm KT2017 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 20 2htsm Kueppers & Bayen 2014 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 21 2htsm M2003 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 22 2htsm MH2001 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 23 2htsm Mieth et al. (2016) TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE FALSE
## 24 2htsm Mieth et al. (2016) Ex1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 25 2htsm Mieth et al. (2016) Ex2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 26 2htsm Mieth et al. (2016) Ex3 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 27 2htsm S2002_E1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 28 2htsm S2002_E2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 29 2htsm S2002_E3 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 30 2htsm Schuetz & Broeder (2011) Ex1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 31 2htsm Schuetz & Broeder (2011) Ex2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 32 2htsm Schuetz & Broeder (2011) Ex3 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 33 2htsm Schuetz & Broeder (2011) Ex4 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 34 2htsm Schuetz & Broeder (2011) Ex5 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 35 2htsm Suessenbach et al. (2016) TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## # A tibble: 15 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 c2ht Benjamin_2013 TRUE TRUE TRUE TRUE TRUE NA NA NA TRUE TRUE
## 2 c2ht Dube_2012-P TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 3 c2ht Dube_2012-W TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 4 c2ht Heathcote_2006_e1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 5 c2ht Heathcote_2006_e2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 6 c2ht Jaeger_2012 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 7 c2ht Jang_2009 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 8 c2ht Koen-2013_full TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 9 c2ht Koen-2013_immediate TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 10 c2ht Koen_2010_pure TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 11 c2ht Koen_2011 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 12 c2ht Onyper_2010-Pics TRUE TRUE TRUE TRUE TRUE NA NA TRUE TRUE TRUE
## 13 c2ht Onyper_2010-Words TRUE TRUE TRUE TRUE TRUE NA NA TRUE TRUE TRUE
## 14 c2ht Pratte_2010 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 15 c2ht Smith_2004 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## # A tibble: 9 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 pc Broeder_sixTrials.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 2 pc Francis_fourTrials_english.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 3 pc Francis_fourTrials_englishDominant.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 4 pc Francis_fourTrials_spanishDominant.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 5 pc GolzErdfelder_sixTrials_afternoon.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 6 pc GolzErdfelder_sixTrials_forenoon.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 7 pc Matzke_fourTrials.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 8 pc Riefer_sixTrials_alcoholics.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 9 pc Riefer_sixTrials_schizos.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## # A tibble: 10 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 pd bodner_2000_exp2.txt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 2 pd bodner_2000_exp4.txt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 3 pd caldwell_masson_2001_exp1.txt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 4 pd caldwell_masson_2001_exp2.txt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 5 pd klauer_2015_exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 6 pd klauer_2015_exp3.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 7 pd klauer_2015_exp5.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
## 8 pd rouder_2008_exp1.dat TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 9 pd rouder_2008_exp2.dat TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 10 pd stahl_2015_exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## # A tibble: 14 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 pm ArnoldBayenBoehm2015_data.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 2 pm Data Schnitzspahn et al 2012.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 3 pm Horn_et_al_2011_Exp2A.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 4 pm Horn_et_al_2011_Exp2B.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 5 pm Pavawalla_etal2012_data.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 6 pm Rummeletal2011_data.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 7 pm Smith & Hunt 2013.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 8 pm Smith et al 2014 Exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 9 pm SmithBayen2005_Experiment1.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 10 pm SmithBayen2005_Experiment2.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 11 pm SmithBayenMartin2010_data.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 12 pm Smithetal2011_VersionArnoldetal2015_d~ TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE NA
## 13 pm Smithetal2014_Exp2.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 14 pm Smithetal2014_Exp3.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## # A tibble: 9 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 hb Bayen2006Exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE FALSE TRUE
## 2 hb Bayen2006Exp2.csv TRUE TRUE TRUE TRUE NA TRUE NA TRUE TRUE TRUE
## 3 hb Bernstein2011.csv TRUE TRUE TRUE TRUE NA TRUE NA TRUE NA TRUE
## 4 hb Coolin2015.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 5 hb Coolin2016.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE NA
## 6 hb ErdfelderBrandtBröder2007Exp1.csv TRUE TRUE TRUE TRUE NA TRUE NA TRUE FALSE TRUE
## 7 hb GroßBayen2015.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 8 hb GroßBayen2017.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE NA NA
## 9 hb Pohl2010.csv TRUE TRUE TRUE TRUE TRUE TRUE NA NA NA TRUE
## # A tibble: 42 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 rm Castela Erdfelder 2017b_Exp1 within1.~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 2 rm Castela Erdfelder 2017b_Exp1 within2.~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 3 rm Castela Erdfelder 2017b_Exp1 within3.~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 4 rm Castela Erdfelder 2017b_Exp2.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 5 rm Data from Filevich Horn Kuehn 2017_wi~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 6 rm Data from Filevich Horn Kuehn 2017_wi~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 7 rm Hilbig et al 2015_exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 8 rm Hilbig et al 2015_exp2.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 9 rm Hilbig et al 2015_exp3.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 10 rm Hilbig Richter.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 11 rm HilbigErdfelderPohl20106.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 12 rm HilbigErdfelderPohl20107b.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 13 rm HilbigErdfelderPohl2011.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 14 rm HilbigErdfelderPohl2012exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 15 rm HilbigPohl09exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 16 rm HilbigPohl09exp2.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 17 rm HilbigPohl09exp3.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 18 rm HilbigPohl2008exp5.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 19 rm HilbigPohlBroeder2009.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 20 rm HilbigSchollPohl2010exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 21 rm HilbigSchollPohl2010exp2.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 22 rm Horn Pachur Mata 2015.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 23 rm Horn Ruggeri Pachur 2016 .csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 24 rm Michalkiewicz Erdfelder 2016_Exp.1_da~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 25 rm Michalkiewicz Erdfelder 2016_Exp.1_da~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 26 rm Michalkiewicz Erdfelder 2016_Exp.1_we~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 27 rm Michalkiewicz Erdfelder 2016_Exp.1_we~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 28 rm Michalkiewicz Erdfelder 2016_Exp.2_da~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 29 rm Michalkiewicz Erdfelder 2016_Exp.2_da~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 30 rm Michalkiewicz Erdfelder 2016_Exp.2_we~ TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 31 rm Michalkiewicz Erdfelder 2016_Exp.2_we~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 32 rm Michalkiewicz Erdfelder 2016_Exp.3_di~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 33 rm Michalkiewicz Erdfelder 2016_Exp.3_di~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 34 rm Michalkiewicz Erdfelder 2016_Exp.3_re~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 35 rm Michalkiewicz Erdfelder 2016_Exp.3_re~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 36 rm Michalkiewicz Erdfelder 2016_Exp.4_na~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 37 rm Michalkiewicz Erdfelder 2016_Exp.4_pi~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 38 rm Michalkiewicz, Arden, Erdfelder 2017.~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 39 rm Pohl et al 2017.csv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 40 rm Pohl, Michalkiewicz, Erdfelder, Hilbi~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 41 rm Pohl, Michalkiewicz, Erdfelder, Hilbi~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## 42 rm PohlErdfelderHilbigLiebkeStahlberg201~ TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## # A tibble: 9 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 real data_KM2015.csv TRUE TRUE TRUE TRUE TRUE FALSE NA TRUE TRUE TRUE
## 2 real data_MR2013_Exp123.csv TRUE TRUE TRUE TRUE TRUE FALSE NA TRUE TRUE TRUE
## 3 real data_MR2013_Exp4.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 4 real data_MR2013_Exp5.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 5 real data_MR2013_Exp6.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 6 real data_MR2013_Exp7.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 7 real data_MR2015b_Exp1.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 8 real data_MR2015b_Exp2.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 9 real data_VMTD2017.csv TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## # A tibble: 21 x 12
## model dataset `Comp MLE` `Comp Bayes` `No asy` `No PB` `No NPB` `No Bayes` `LC PP` `Beta PP` `Trait_u PP` `Trait PP`
## <fct> <chr> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
## 1 quad BeerEtAl2008 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 2 quad CalanchiniEtAl2013 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 3 quad CalanchiniEtAl2014_1a_AsianWhite TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 4 quad CalanchiniEtAl2014_1a_BlackWhite TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 5 quad CalanchiniEtAl2014_1b_BlackWhite TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 6 quad CalanchiniEtAl2014_1b_FlowerInsect TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 7 quad CalanchiniEtAl2014_1c_FlowerInsect TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 8 quad CalanchiniEtAl2014_1c_Stereotype TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 9 quad CalanchiniEtAl2014_PI_ableMCMC TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE FALSE TRUE
## 10 quad CalanchiniEtAl2014_PI_ageMCMC TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 11 quad CalanchiniEtAl2014_PI_careerMCMC TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 12 quad CalanchiniEtAl2014_PI_raceMCMC TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 13 quad CalanchiniEtAl2014_PI_skinMCMC TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 14 quad CalanchiniEtAl2014_PI_straightMCMC TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 15 quad GonsalkoraleEtAl2011 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 16 quad JinEtAl2016s1 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 17 quad JinEtAl2016s2 TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 18 quad LuekeGibson2015age TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 19 quad LuekeGibson2015race TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 20 quad WrzusEtAl_HappyUnhappy TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE TRUE
## 21 quad WrzusEtAl_NumberLetter TRUE TRUE TRUE TRUE TRUE TRUE NA TRUE TRUE NACore Parameters Per Model
The following gives an overview of the core and (if present) non-core parameters for each model.
## 2htsm
## Core parameters:
## b d D g d_1 d_2 D_1 D_2
##
## c2ht
## Core parameters:
## Dn Do g
## Non-core parameters:
## q_1 q_2 q_5 q_6 r_1 r_2 r_6 q_3 q_7 q_8 r_3 r_8
##
## pc
## Core parameters:
## c r u
##
## pd
## Core parameters:
## A C A_alt C_Inclusion C_Exclusion
##
## pm
## Core parameters:
## C1 C2 M P
##
## hb
## Core parameters:
## b c rc re
## Non-core parameters:
## gg1 gg2 gg3 gl1 gl2 gl3 h2 lc le
##
## rm
## Core parameters:
## a b g r
##
## real
## Core parameters:
## A1 A2 L1 L2 L3 L4 Re
## Non-core parameters:
## attL attReC attReT
##
## quad
## Core parameters:
## ACbb1 ACwg1 D1 G1 OB1Core Parameters Per Submodel
The following gives an overview of the core and (if present) non-core parameters for each submodel.
## 2htsm_4
## Core parameters:
## b d D g
##
## 2htsm_5d
## Core parameters:
## b D d_1 d_2 g
##
## 2htsm_6e
## Core parameters:
## b d_1 D_1 d_2 D_2 g
##
## c2ht6
## Core parameters:
## Dn Do g
## Non-core parameters:
## q_1 q_2 q_5 q_6 r_1 r_2 r_6
##
## c2ht8
## Core parameters:
## Dn Do g
## Non-core parameters:
## q_1 q_2 q_3 q_6 q_7 q_8 r_1 r_2 r_3 r_8
##
## pc
## Core parameters:
## c r u
##
## pd_s
## Core parameters:
## A C
##
## pd_e
## Core parameters:
## A_alt C_Inclusion C_Exclusion
##
## pm
## Core parameters:
## C1 C2 M P
##
## hb
## Core parameters:
## b c rc re
## Non-core parameters:
## gg1 gg2 gg3 gl1 gl2 gl3 h2 lc le
##
## rm
## Core parameters:
## a b g r
##
## real
## Core parameters:
## A1 A2 L1 L2 L3 L4 Re
## Non-core parameters:
## attL attReC attReT
##
## quad
## Core parameters:
## ACbb1 ACwg1 D1 G1 OB1Pairwise Plots of Core Parameters
We plot the core parameters for each condition that are usable in the following plot.
All Pairwise Plots
We can also plot all pairwise plots (instead of only the upper half of the pairs-matrix) and overlay each plot with a GAM.
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'