Construal Level International Multilab Replication (CLIMR) Project: Exploration of Item-Level Effects on the BIF
CLIMR Team 2025-01-07
knitr::include_graphics("./figures/climr_bif-items.png")
knitr::include_graphics("./figures/climr_bif-items-rma.png")
item_effects_temporal## # A tibble: 19 × 4
## item d ci_lb ci_ub
## <chr> <dbl> <dbl> <dbl>
## 1 bif_01 0.0135 -0.0588 0.0858
## 2 bif_02 0.112 0.0399 0.185
## 3 bif_04 -0.0385 -0.111 0.0338
## 4 bif_07 0.0637 -0.00865 0.136
## 5 bif_08 0.0383 -0.0341 0.111
## 6 bif_09 0.00693 -0.0654 0.0793
## 7 bif_10 0.233 0.160 0.306
## 8 bif_11 0.252 0.179 0.324
## 9 bif_12 -0.0687 -0.141 0.00371
## 10 bif_15 -0.0622 -0.135 0.0102
## 11 bif_16 -0.0692 -0.142 0.00313
## 12 bif_17 0.0310 -0.0413 0.103
## 13 bif_18 -0.0245 -0.0968 0.0479
## 14 bif_19 0.00621 -0.0661 0.0786
## 15 bif_20 -0.0611 -0.133 0.0113
## 16 bif_22 0.233 0.160 0.306
## 17 bif_23 0.0365 -0.0359 0.109
## 18 bif_24 0.101 0.0287 0.173
## 19 bif_25 -0.0825 -0.155 -0.0101
meta_temporal_bif_item##
## Multivariate Meta-Analysis Model (k = 1493; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.0170 0.1305 79 no lab_modality
##
## Test for Residual Heterogeneity:
## QE(df = 1474) = 1503.4545, p-val = 0.2908
##
## Test of Moderators (coefficients 1:19):
## QM(df = 19) = 154.1068, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## itembif_01 0.0051 0.0402 0.1268 0.8991 -0.0736 0.0838
## itembif_02 0.1000 0.0403 2.4847 0.0130 0.0211 0.1789 *
## itembif_04 -0.0505 0.0402 -1.2560 0.2091 -0.1293 0.0283
## itembif_07 0.0538 0.0401 1.3398 0.1803 -0.0249 0.1325
## itembif_08 0.0385 0.0404 0.9548 0.3397 -0.0406 0.1176
## itembif_09 -0.0007 0.0403 -0.0182 0.9854 -0.0797 0.0783
## itembif_10 0.2274 0.0404 5.6212 <.0001 0.1481 0.3066 ***
## itembif_11 0.2441 0.0406 6.0087 <.0001 0.1645 0.3237 ***
## itembif_12 -0.0793 0.0402 -1.9739 0.0484 -0.1580 -0.0006 *
## itembif_15 -0.0795 0.0402 -1.9802 0.0477 -0.1582 -0.0008 *
## itembif_16 -0.0863 0.0402 -2.1502 0.0315 -0.1650 -0.0076 *
## itembif_17 0.0168 0.0402 0.4175 0.6763 -0.0619 0.0955
## itembif_18 -0.0380 0.0402 -0.9470 0.3436 -0.1168 0.0407
## itembif_19 -0.0026 0.0401 -0.0652 0.9480 -0.0813 0.0761
## itembif_20 -0.0789 0.0401 -1.9649 0.0494 -0.1576 -0.0002 *
## itembif_22 0.2272 0.0404 5.6247 <.0001 0.1480 0.3063 ***
## itembif_23 0.0280 0.0402 0.6951 0.4870 -0.0509 0.1068
## itembif_24 0.0906 0.0402 2.2562 0.0241 0.0119 0.1693 *
## itembif_25 -0.0975 0.0402 -2.4289 0.0151 -0.1763 -0.0188 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
item_effects_spatial## # A tibble: 13 × 4
## item d ci_lb ci_ub
## <chr> <dbl> <dbl> <dbl>
## 1 bif_02 0.0453 -0.0266 0.117
## 2 bif_04 -0.00498 -0.0769 0.0670
## 3 bif_05 0.0626 -0.00935 0.135
## 4 bif_07 0.00190 -0.0700 0.0738
## 5 bif_09 0.00469 -0.0673 0.0766
## 6 bif_10 0.0450 -0.0269 0.117
## 7 bif_12 -0.00723 -0.0792 0.0647
## 8 bif_14 0.0467 -0.0253 0.119
## 9 bif_16 -0.0283 -0.100 0.0436
## 10 bif_19 0.0163 -0.0557 0.0882
## 11 bif_20 0.00350 -0.0684 0.0754
## 12 bif_22 0.00545 -0.0665 0.0774
## 13 bif_23 0.0279 -0.0441 0.0998
meta_spatial_bif_item##
## Multivariate Meta-Analysis Model (k = 1018; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.0107 0.1035 79 no lab_modality
##
## Test for Residual Heterogeneity:
## QE(df = 1005) = 1033.1191, p-val = 0.2623
##
## Test of Moderators (coefficients 1:13):
## QM(df = 13) = 9.3174, p-val = 0.7486
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## itembif_02 0.0474 0.0391 1.2122 0.2254 -0.0292 0.1240
## itembif_04 0.0033 0.0390 0.0847 0.9325 -0.0731 0.0797
## itembif_05 0.0676 0.0390 1.7337 0.0830 -0.0088 0.1440 .
## itembif_07 0.0044 0.0390 0.1126 0.9104 -0.0720 0.0808
## itembif_09 0.0047 0.0390 0.1192 0.9051 -0.0718 0.0811
## itembif_10 0.0656 0.0392 1.6706 0.0948 -0.0114 0.1425 .
## itembif_12 -0.0079 0.0394 -0.2013 0.8405 -0.0852 0.0693
## itembif_14 0.0515 0.0389 1.3232 0.1858 -0.0248 0.1277
## itembif_16 -0.0271 0.0390 -0.6948 0.4872 -0.1036 0.0494
## itembif_19 0.0149 0.0391 0.3806 0.7035 -0.0617 0.0915
## itembif_20 0.0090 0.0395 0.2268 0.8206 -0.0684 0.0864
## itembif_22 0.0022 0.0391 0.0557 0.9556 -0.0745 0.0789
## itembif_23 0.0346 0.0390 0.8872 0.3750 -0.0418 0.1110
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
item_effects_social## # A tibble: 25 × 4
## item d ci_lb ci_ub
## <chr> <dbl> <dbl> <dbl>
## 1 bif_01 -0.200 -0.273 -0.127
## 2 bif_02 -0.324 -0.397 -0.251
## 3 bif_03 0.0863 0.0137 0.159
## 4 bif_04 0.135 0.0619 0.207
## 5 bif_05 0.0405 -0.0321 0.113
## 6 bif_06 0.0325 -0.0401 0.105
## 7 bif_07 -0.166 -0.239 -0.0938
## 8 bif_08 -0.0222 -0.0948 0.0503
## 9 bif_09 -0.199 -0.271 -0.126
## 10 bif_10 -0.148 -0.220 -0.0749
## # ℹ 15 more rows
meta_social_bif_item##
## Multivariate Meta-Analysis Model (k = 1965; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.0190 0.1379 79 no lab_modality
##
## Test for Residual Heterogeneity:
## QE(df = 1940) = 2278.0755, p-val < .0001
##
## Test of Moderators (coefficients 1:25):
## QM(df = 25) = 285.1660, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## itembif_01 -0.1973 0.0407 -4.8440 <.0001 -0.2771 -0.1175 ***
## itembif_02 -0.3188 0.0409 -7.7922 <.0001 -0.3990 -0.2386 ***
## itembif_03 0.0984 0.0407 2.4207 0.0155 0.0187 0.1781 *
## itembif_04 0.1516 0.0407 3.7275 0.0002 0.0719 0.2312 ***
## itembif_05 0.0555 0.0406 1.3648 0.1723 -0.0242 0.1351
## itembif_06 0.0498 0.0406 1.2260 0.2202 -0.0298 0.1294
## itembif_07 -0.1557 0.0407 -3.8245 0.0001 -0.2355 -0.0759 ***
## itembif_08 -0.0136 0.0406 -0.3338 0.7385 -0.0932 0.0661
## itembif_09 -0.1847 0.0407 -4.5340 <.0001 -0.2645 -0.1048 ***
## itembif_10 -0.1405 0.0407 -3.4500 0.0006 -0.2204 -0.0607 ***
## itembif_11 0.0442 0.0410 1.0776 0.2812 -0.0362 0.1245
## itembif_12 -0.1096 0.0407 -2.6949 0.0070 -0.1893 -0.0299 **
## itembif_13 -0.0658 0.0406 -1.6196 0.1053 -0.1455 0.0138
## itembif_14 -0.1481 0.0406 -3.6463 0.0003 -0.2277 -0.0685 ***
## itembif_15 -0.2435 0.0408 -5.9725 <.0001 -0.3234 -0.1636 ***
## itembif_16 -0.1279 0.0406 -3.1470 0.0016 -0.2075 -0.0482 **
## itembif_17 -0.0991 0.0407 -2.4323 0.0150 -0.1790 -0.0192 *
## itembif_18 -0.2357 0.0408 -5.7809 <.0001 -0.3157 -0.1558 ***
## itembif_19 -0.2712 0.0409 -6.6393 <.0001 -0.3513 -0.1912 ***
## itembif_20 -0.2463 0.0408 -6.0391 <.0001 -0.3263 -0.1664 ***
## itembif_21 -0.0114 0.0407 -0.2808 0.7789 -0.0911 0.0683
## itembif_22 -0.1445 0.0408 -3.5400 0.0004 -0.2245 -0.0645 ***
## itembif_23 -0.0436 0.0406 -1.0745 0.2826 -0.1232 0.0360
## itembif_24 -0.0910 0.0406 -2.2432 0.0249 -0.1705 -0.0115 *
## itembif_25 -0.0622 0.0406 -1.5329 0.1253 -0.1416 0.0173
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
item_effects_likelihood## # A tibble: 9 × 4
## item d ci_lb ci_ub
## <chr> <dbl> <dbl> <dbl>
## 1 bif_01 0.0250 -0.0474 0.0974
## 2 bif_07 0.0247 -0.0476 0.0971
## 3 bif_08 0.0764 0.00398 0.149
## 4 bif_09 0.0409 -0.0315 0.113
## 5 bif_11 0.0354 -0.0370 0.108
## 6 bif_12 -0.0153 -0.0877 0.0571
## 7 bif_18 0.0165 -0.0558 0.0889
## 8 bif_22 -0.0408 -0.113 0.0316
## 9 bif_25 0.0206 -0.0518 0.0930
meta_likelihood_bif_item##
## Multivariate Meta-Analysis Model (k = 702; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.0176 0.1328 78 no lab_modality
##
## Test for Residual Heterogeneity:
## QE(df = 693) = 779.9094, p-val = 0.0119
##
## Test of Moderators (coefficients 1:9):
## QM(df = 9) = 7.2821, p-val = 0.6078
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## itembif_01 0.0215 0.0405 0.5313 0.5952 -0.0578 0.1008
## itembif_07 0.0242 0.0405 0.5983 0.5496 -0.0551 0.1036
## itembif_08 0.0790 0.0405 1.9492 0.0513 -0.0004 0.1585 .
## itembif_09 0.0288 0.0405 0.7121 0.4764 -0.0505 0.1082
## itembif_11 0.0347 0.0405 0.8585 0.3906 -0.0446 0.1141
## itembif_12 -0.0158 0.0405 -0.3906 0.6961 -0.0952 0.0636
## itembif_18 0.0162 0.0406 0.3988 0.6901 -0.0633 0.0957
## itembif_22 -0.0428 0.0405 -1.0591 0.2895 -0.1221 0.0364
## itembif_25 0.0121 0.0405 0.2982 0.7655 -0.0672 0.0914
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1