Rscript : ΓöÇΓöÇ Attaching core tidyverse packages ΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇ tidyverse 2.0.0 ΓöÇΓöÇ At line:1 char:13 + cd "eohi2"; Rscript "mixed anova - domain means.r" > "results exp2 - ... + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + CategoryInfo : NotSpecified: (ΓöÇΓöÇ Attachin...se 2.0.0 ΓöÇΓöÇ :String) [], RemoteException + FullyQualifiedErrorId : NativeCommandError Γ£ö dplyr 1.1.4 Γ£ö readr 2.1.5 Γ£ö forcats 1.0.0 Γ£ö stringr 1.5.1 Γ£ö ggplot2 3.5.1 Γ£ö tibble 3.2.1 Γ£ö lubridate 1.9.3 Γ£ö tidyr 1.3.1 Γ£ö purrr 1.0.2 ΓöÇΓöÇ Conflicts ΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓö ÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇ tidyverse_conflicts() ΓöÇΓöÇ Γ£û dplyr::filter() masks stats::filter() Γ£û dplyr::lag() masks stats::lag() Γä╣ Use the conflicted package () to force all conflicts to become errors Loading required package: carData Attaching package: 'car' The following object is masked from 'package:dplyr': recode The following object is masked from 'package:purrr': some Loading required package: lme4 Loading required package: Matrix Attaching package: 'Matrix' The following objects are masked from 'package:tidyr': expand, pack, unpack ************ Welcome to afex. For support visit: http://afex.singmann.science/ - Functions for ANOVAs: aov_car(), aov_ez(), and aov_4() - Methods for calculating p-values with mixed(): 'S', 'KR', 'LRT', and 'PB' - 'afex_aov' and 'mixed' objects can be passed to emmeans() for follow-up tests - Get and set global package options with: afex_options() - Set sum-to-zero contrasts globally: set_sum_contrasts() - For example analyses see: browseVignettes("afex") ************ Attaching package: 'afex' The following object is masked from 'package:lme4': lmer Welcome to emmeans. Caution: You lose important information if you filter this package's results. See '? untidy' Warning message: package 'effsize' was built under R version 4.4.3 Registered S3 methods overwritten by 'parameters': method from display.parameters_distribution datawizard plot.parameters_distribution datawizard print_md.parameters_distribution datawizard [1] "Dataset dimensions: 490 x213" [1] "Number of participants: 490" [1] "All required domain mean variables found!" [1] "Domain mapping created:" variable time domain interval 1 NPast_5_pref_MEAN Past Preferences 5 2 NPast_5_pers_MEAN Past Personality 5 3 NPast_5_val_MEAN Past Values 5 4 NPast_10_pref_MEAN Past Preferences 10 5 NPast_10_pers_MEAN Past Personality 10 6 NPast_10_val_MEAN Past Values 10 7 NFut_5_pref_MEAN Future Preferences 5 8 NFut_5_pers_MEAN Future Personality 5 9 NFut_5_val_MEAN Future Values 5 10 NFut_10_pref_MEAN Future Preferences 10 11 NFut_10_pers_MEAN Future Personality 10 12 NFut_10_val_MEAN Future Values 10 13 X5.10past_pref_MEAN Past Preferences 5_10 14 X5.10past_pers_MEAN Past Personality 5_10 15 X5.10past_val_MEAN Past Values 5_10 16 X5.10fut_pref_MEAN Future Preferences 5_10 17 X5.10fut_pers_MEAN Future Personality 5_10 18 X5.10fut_val_MEAN Future Values 5_10 [1] "Long data dimensions: 8820 x7" [1] "Number of participants: 490" [1] "Descriptive statistics by TIME, DOMAIN, and INTERVAL:" # A tibble: 18 ├ù 12 TIME DOMAIN INTERVAL n mean variance sd median q1 q3 min 1 Past PreferenΓǪ 5 490 0.656 0.420 0.648 0.4 0.2 1 0 2 Past PreferenΓǪ 10 490 0.795 0.490 0.700 0.6 0.2 1.2 0 3 Past PreferenΓǪ 5_10 490 0.592 0.388 0.623 0.4 0.05 1 0 4 Past PersonalΓǪ 5 490 0.961 0.569 0.755 0.8 0.4 1.4 0 5 Past PersonalΓǪ 10 490 1.05 0.624 0.790 0.8 0.4 1.4 0 6 Past PersonalΓǪ 5_10 490 0.769 0.531 0.729 0.6 0.2 1.2 0 7 Past Values 5 490 0.673 0.439 0.662 0.6 0.2 1 0 8 Past Values 10 490 0.818 0.630 0.793 0.6 0.2 1.2 0 9 Past Values 5_10 490 0.595 0.458 0.677 0.4 0 0.8 0 10 Future PreferenΓǪ 5 490 0.580 0.346 0.588 0.4 0.2 0.8 0 11 Future PreferenΓǪ 10 490 0.692 0.380 0.617 0.6 0.2 1 0 12 Future PreferenΓǪ 5_10 490 0.457 0.325 0.570 0.4 0 0.6 0 13 Future PersonalΓǪ 5 490 0.886 0.458 0.677 0.8 0.4 1.2 0 14 Future PersonalΓǪ 10 490 0.925 0.468 0.684 0.8 0.4 1.2 0 15 Future PersonalΓǪ 5_10 490 0.581 0.345 0.587 0.4 0.2 0.8 0 16 Future Values 5 490 0.620 0.334 0.578 0.4 0.2 0.8 0 17 Future Values 10 490 0.674 0.378 0.615 0.6 0.2 1 0 18 Future Values 5_10 490 0.471 0.324 0.569 0.3 0 0.8 0 # Γä╣ 1 more variable: max [1] "Descriptive statistics by between-subjects factors:" # A tibble: 72 ├ù 9 TEMPORAL_DO INTERVAL_DO TIME DOMAIN INTERVAL n mean variance sd 1 01PAST 5 Past PreferencΓǪ 5 118 0.563 0.331 0.575 2 01PAST 5 Past PreferencΓǪ 10 118 0.725 0.409 0.640 3 01PAST 5 Past PreferencΓǪ 5_10 118 0.569 0.360 0.600 4 01PAST 5 Past PersonaliΓǪ 5 118 0.883 0.605 0.778 5 01PAST 5 Past PersonaliΓǪ 10 118 0.969 0.464 0.681 6 01PAST 5 Past PersonaliΓǪ 5_10 118 0.771 0.422 0.650 7 01PAST 5 Past Values 5 118 0.595 0.300 0.548 8 01PAST 5 Past Values 10 118 0.859 0.780 0.883 9 01PAST 5 Past Values 5_10 118 0.593 0.520 0.721 10 01PAST 5 Future PreferencΓǪ 5 118 0.578 0.260 0.510 # Γä╣ 62 more rows [1] "Descriptive statistics by between-subjects factors only:" # A tibble: 4 ├ù 6 TEMPORAL_DO INTERVAL_DO n mean variance sd 1 01PAST 5 2124 0.676 0.432 0.657 2 01PAST 10 2250 0.743 0.470 0.686 3 02FUT 5 2538 0.741 0.471 0.687 4 02FUT 10 1908 0.671 0.481 0.693 [1] "Data after removing missing values: 8820 x7" [1] "Missing values by TIME, DOMAIN, and INTERVAL:" # A tibble: 18 ├ù 6 TIME DOMAIN INTERVAL n_total n_missing pct_missing 1 Past Preferences 5 490 0 0 2 Past Preferences 10 490 0 0 3 Past Preferences 5_10 490 0 0 4 Past Personality 5 490 0 0 5 Past Personality 10 490 0 0 6 Past Personality 5_10 490 0 0 7 Past Values 5 490 0 0 8 Past Values 10 490 0 0 9 Past Values 5_10 490 0 0 10 Future Preferences 5 490 0 0 11 Future Preferences 10 490 0 0 12 Future Preferences 5_10 490 0 0 13 Future Personality 5 490 0 0 14 Future Personality 10 490 0 0 15 Future Personality 5_10 490 0 0 16 Future Values 5 490 0 0 17 Future Values 10 490 0 0 18 Future Values 5_10 490 0 0 [1] "Outlier summary (IQR method):" # A tibble: 18 ├ù 12 TIME DOMAIN INTERVAL n mean sd q1 q3 iqr lower_bound 1 Past Preferences 5 490 0.656 0.648 0.2 1 0.8 -1 2 Past Preferences 10 490 0.795 0.700 0.2 1.2 1 -1.3 3 Past Preferences 5_10 490 0.592 0.623 0.05 1 0.95 -1.37 4 Past Personality 5 490 0.961 0.755 0.4 1.4 1 -1.1 5 Past Personality 10 490 1.05 0.790 0.4 1.4 1 -1.1 6 Past Personality 5_10 490 0.769 0.729 0.2 1.2 1 -1.3 7 Past Values 5 490 0.673 0.662 0.2 1 0.8 -1 8 Past Values 10 490 0.818 0.793 0.2 1.2 1 -1.3 9 Past Values 5_10 490 0.595 0.677 0 0.8 0.8 -1.2 10 Future Preferences 5 490 0.580 0.588 0.2 0.8 0.6 -0.7 11 Future Preferences 10 490 0.692 0.617 0.2 1 0.8 -1 12 Future Preferences 5_10 490 0.457 0.570 0 0.6 0.6 -0.9 13 Future Personality 5 490 0.886 0.677 0.4 1.2 0.8 -0.8 14 Future Personality 10 490 0.925 0.684 0.4 1.2 0.8 -0.8 15 Future Personality 5_10 490 0.581 0.587 0.2 0.8 0.6 -0.7 16 Future Values 5 490 0.620 0.578 0.2 0.8 0.6 -0.7 17 Future Values 10 490 0.674 0.615 0.2 1 0.8 -1 18 Future Values 5_10 490 0.471 0.569 0 0.8 0.8 -1.2 # Γä╣ 2 more variables: upper_bound , n_outliers [1] "Anderson-Darling normality test results:" # A tibble: 18 ├ù 6 TIME DOMAIN INTERVAL n ad_statistic ad_p_value 1 Past Preferences 5 490 18.2 0 2 Past Preferences 10 490 12.9 0 3 Past Preferences 5_10 490 22.7 0 4 Past Personality 5 490 10.6 0 5 Past Personality 10 490 10.7 0 6 Past Personality 5_10 490 17.4 0 7 Past Values 5 490 19.8 0 8 Past Values 10 490 18.9 0 9 Past Values 5_10 490 24.1 0 10 Future Preferences 5 490 19.5 0 11 Future Preferences 10 490 13.6 0 12 Future Preferences 5_10 490 29.1 0 13 Future Personality 5 490 10.9 0 14 Future Personality 10 490 8.87 0 15 Future Personality 5_10 490 18.5 0 16 Future Values 5 490 17.2 0 17 Future Values 10 490 16.1 0 18 Future Values 5_10 490 28.3 0 [1] "Homogeneity of variance across TIME within each DOMAIN ├ù INTERVAL combination:" # A tibble: 9 ├ù 4 DOMAIN INTERVAL levene_F levene_p 1 Preferences 5 3.31 0.0692 2 Preferences 10 7.21 0.00736 3 Preferences 5_10 7.16 0.00760 4 Personality 5 2.67 0.103 5 Personality 10 9.15 0.00255 6 Personality 5_10 10.8 0.00107 7 Values 5 3.75 0.0532 8 Values 10 15.6 0.0000852 9 Values 5_10 4.93 0.0266 [1] "Homogeneity of variance across DOMAIN within each TIME ├ù INTERVAL combination:" # A tibble: 6 ├ù 4 TIME INTERVAL levene_F levene_p 1 Past 5 6.01 0.00250 2 Past 10 2.91 0.0546 3 Past 5_10 2.32 0.0983 4 Future 5 8.33 0.000252 5 Future 10 3.98 0.0190 6 Future 5_10 0.913 0.401 [1] "Homogeneity of variance across INTERVAL within each TIME ├ù DOMAIN combination:" # A tibble: 6 ├ù 4 TIME DOMAIN levene_F levene_p 1 Past Preferences 2.54 0.0793 2 Past Personality 2.86 0.0575 3 Past Values 5.11 0.00615 4 Future Preferences 2.03 0.131 5 Future Personality 5.88 0.00285 6 Future Values 0.589 0.555 [1] "\n=== HARTLEY'S F-MAX TEST FOR BETWEEN-SUBJECTS FACTORS ===" [1] "Unique TEMPORAL_DO values:" [1] 02FUT 01PAST Levels: 01PAST 02FUT [1] "Unique INTERVAL_DO values:" [1] 5 10 Levels: 5 10 [1] "\n=== HARTLEY'S F-MAX TEST: TEMPORAL_DO within each TIME ├ù DOMAIN ├ù INTERVAL combination ===" # A tibble: 18 ├ù 6 TIME DOMAIN INTERVAL past_var fut_var f_max_ratio 1 Past Preferences 5 0.321 0.516 1.61 2 Past Preferences 10 0.439 0.543 1.24 3 Past Preferences 5_10 0.405 0.370 1.10 4 Past Personality 5 0.525 0.609 1.16 5 Past Personality 10 0.573 0.671 1.17 6 Past Personality 5_10 0.483 0.579 1.20 7 Past Values 5 0.401 0.473 1.18 8 Past Values 10 0.693 0.570 1.22 9 Past Values 5_10 0.552 0.363 1.52 10 Future Preferences 5 0.338 0.352 1.04 11 Future Preferences 10 0.366 0.395 1.08 12 Future Preferences 5_10 0.402 0.250 1.61 13 Future Personality 5 0.461 0.451 1.02 14 Future Personality 10 0.452 0.484 1.07 15 Future Personality 5_10 0.303 0.382 1.26 16 Future Values 5 0.322 0.345 1.07 17 Future Values 10 0.366 0.391 1.07 18 Future Values 5_10 0.311 0.334 1.07 [1] "\n=== HARTLEY'S F-MAX TEST: INTERVAL_DO within each TIME ├ù DOMAIN ├ù TEMPORAL_DO combination ===" # A tibble: 12 ├ù 6 TIME DOMAIN TEMPORAL_DO int5_var int10_var f_max_ratio 1 Past Preferences 01PAST 0.370 0.411 1.11 2 Past Preferences 02FUT 0.548 0.398 1.38 3 Past Personality 01PAST 0.501 0.564 1.13 4 Past Personality 02FUT 0.625 0.658 1.05 5 Past Values 01PAST 0.546 0.565 1.03 6 Past Values 02FUT 0.449 0.522 1.16 7 Future Preferences 01PAST 0.296 0.452 1.53 8 Future Preferences 02FUT 0.329 0.351 1.07 9 Future Personality 01PAST 0.459 0.423 1.09 10 Future Personality 02FUT 0.423 0.486 1.15 11 Future Values 01PAST 0.350 0.340 1.03 12 Future Values 02FUT 0.355 0.364 1.03 [1] "Data size for ANOVA: 8820 rows" [1] "Number of participants: 490" [1] "Design factors: TIME (2), DOMAIN (3), INTERVAL (3), TEMPORAL_DO (2), INTERVAL_DO (2)" [1] "Complete cases: 8820 out of 8820" [1] "Design is balanced: each participant has data for all TIME ├ù DOMAIN ├ù INTERVAL combinations" [1] "\n=== MIXED ANOVA RESULTS (with sphericity corrections) ===" Warning: Data is unbalanced (unequal N per group). Make sure you specified a well-considered value for the type argument to ezANOVA(). [1] "ANOVA Results:" Effect DFn DFd SSn 1 (Intercept) 1 486 4370.212440908 2 TEMPORAL_DO 1 486 0.021739890 3 INTERVAL_DO 1 486 0.002941091 4 TIME 1 486 28.467598229 5 DOMAIN 2 972 99.251774422 6 INTERVAL 2 972 90.823692462 7 TEMPORAL_DO:INTERVAL_DO 1 486 10.260283379 8 TEMPORAL_DO:TIME 1 486 0.908911971 9 INTERVAL_DO:TIME 1 486 0.065900104 10 TEMPORAL_DO:DOMAIN 2 972 0.704765040 11 INTERVAL_DO:DOMAIN 2 972 0.039169995 12 TEMPORAL_DO:INTERVAL 2 972 0.020747610 13 INTERVAL_DO:INTERVAL 2 972 0.421544230 14 TIME:DOMAIN 2 972 0.249170445 15 TIME:INTERVAL 2 972 2.716461526 16 DOMAIN:INTERVAL 4 1944 7.053010791 17 TEMPORAL_DO:INTERVAL_DO:TIME 1 486 0.288068727 18 TEMPORAL_DO:INTERVAL_DO:DOMAIN 2 972 1.119913999 19 TEMPORAL_DO:INTERVAL_DO:INTERVAL 2 972 0.254201308 20 TEMPORAL_DO:TIME:DOMAIN 2 972 0.549252632 21 INTERVAL_DO:TIME:DOMAIN 2 972 0.362619698 22 TEMPORAL_DO:TIME:INTERVAL 2 972 8.025061793 23 INTERVAL_DO:TIME:INTERVAL 2 972 0.028077397 24 TEMPORAL_DO:DOMAIN:INTERVAL 4 1944 0.470968869 25 INTERVAL_DO:DOMAIN:INTERVAL 4 1944 0.206677935 26 TIME:DOMAIN:INTERVAL 4 1944 0.635703839 27 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN 2 972 0.469481025 28 TEMPORAL_DO:INTERVAL_DO:TIME:INTERVAL 2 972 0.268682073 29 TEMPORAL_DO:INTERVAL_DO:DOMAIN:INTERVAL 4 1944 0.526685599 30 TEMPORAL_DO:TIME:DOMAIN:INTERVAL 4 1944 0.513925813 31 INTERVAL_DO:TIME:DOMAIN:INTERVAL 4 1944 0.712950046 32 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN:INTERVAL 4 1944 0.397866653 SSd F 1 1594.9943 1331.6180922967 2 1594.9943 0.0066242160 3 1594.9943 0.0008961601 4 343.1100 40.3230861714 5 543.4204 88.7643519328 6 290.6823 151.8506990753 7 1594.9943 3.1263420633 8 343.1100 1.2874333636 9 343.1100 0.0933445646 10 543.4204 0.6302961574 11 543.4204 0.0350311035 12 290.6823 0.0346885165 13 290.6823 0.7047917147 14 278.4448 0.4349042433 15 192.3819 6.8623919056 16 321.8394 10.6505403408 17 343.1100 0.4080365331 18 543.4204 1.0015784699 19 290.6823 0.4250063540 20 278.4448 0.9586702791 21 278.4448 0.6329195471 22 192.3819 20.2731084416 23 192.3819 0.0709298120 24 321.8394 0.7111959823 25 321.8394 0.3120981587 26 274.0331 1.1274262125 27 278.4448 0.8194362282 28 192.3819 0.6787512596 29 321.8394 0.7953321474 30 274.0331 0.9114518385 31 274.0331 1.2644230237 32 274.0331 0.7056199235 p 1 0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000002624874 2 0.935165875382395928028245180030353367328643798828125000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 3 0.976130436854070193675170230562798678874969482421875000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 4 0.000000000494752379720093791917040482175593751890119165182113647460937500000000000000000000000000000000000000000000000000000000000000000000000000000 5 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0.965576602035804198997936964588006958365440368652343750000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 12 0.965907428934907441586688037205021828413009643554687500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 13 0.494463883126545822310760058826417662203311920166015625000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 14 0.647452550541005034112629346054745838046073913574218750000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 15 0.001097858070070122397596246166528999310685321688652038574218750000000000000000000000000000000000000000000000000000000000000000000000000000000000000 16 0.000000015427827931898662551339629356306204499560408294200897216796875000000000000000000000000000000000000000000000000000000000000000000000000000000 17 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0.931532093001501859674817751511000096797943115234375000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 24 0.584233147443363964868012772058136761188507080078125000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 25 0.870028308786385706774524351203581318259239196777343750000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 26 0.341742152423954059781152636787737719714641571044921875000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 27 0.440984220627331668929116403887746855616569519042968750000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 28 0.507490277515908916328157829411793500185012817382812500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 29 0.528108513831667680804571318731177598237991333007812500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 30 0.456283954872903074750922769453609362244606018066406250000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 31 0.281829639990916591685277126089204102754592895507812500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 32 0.588061253339402734141572182124946266412734985351562500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 p<.05 ges 1 * 0.5323607343737 2 0.0000056630107 3 0.0000007661268 4 * 0.0073609636770 5 * 0.0252025882320 6 * 0.0231119426518 7 0.0026655857469 8 0.0002367072214 9 0.0000171660803 10 0.0001835511571 11 0.0000102033216 12 0.0000054045338 13 0.0001097963641 14 0.0000649024121 15 * 0.0007071130479 16 * 0.0018338755979 17 0.0000750336411 18 0.0002916422855 19 0.0000662127341 20 0.0001430548253 21 0.0000944501969 22 * 0.0020860943952 23 0.0000073138520 24 0.0001226680384 25 0.0000538348155 26 0.0001655676251 27 0.0001222805636 28 0.0000699843272 29 0.0001371779665 30 0.0001338550595 31 0.0001856824892 32 0.0001036298881 [1] "\nMauchly's Test of Sphericity:" Effect W 9 DOMAIN 0.9893588 10 TEMPORAL_DO:DOMAIN 0.9893588 11 INTERVAL_DO:DOMAIN 0.9893588 12 TEMPORAL_DO:INTERVAL_DO:DOMAIN 0.9893588 13 INTERVAL 0.8413682 14 TEMPORAL_DO:INTERVAL 0.8413682 15 INTERVAL_DO:INTERVAL 0.8413682 16 TEMPORAL_DO:INTERVAL_DO:INTERVAL 0.8413682 17 TIME:DOMAIN 0.9734470 18 TEMPORAL_DO:TIME:DOMAIN 0.9734470 19 INTERVAL_DO:TIME:DOMAIN 0.9734470 20 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN 0.9734470 21 TIME:INTERVAL 0.9756445 22 TEMPORAL_DO:TIME:INTERVAL 0.9756445 23 INTERVAL_DO:TIME:INTERVAL 0.9756445 24 TEMPORAL_DO:INTERVAL_DO:TIME:INTERVAL 0.9756445 25 DOMAIN:INTERVAL 0.7789589 26 TEMPORAL_DO:DOMAIN:INTERVAL 0.7789589 27 INTERVAL_DO:DOMAIN:INTERVAL 0.7789589 28 TEMPORAL_DO:INTERVAL_DO:DOMAIN:INTERVAL 0.7789589 29 TIME:DOMAIN:INTERVAL 0.8745913 30 TEMPORAL_DO:TIME:DOMAIN:INTERVAL 0.8745913 31 INTERVAL_DO:TIME:DOMAIN:INTERVAL 0.8745913 32 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN:INTERVAL 0.8745913 p p<.05 9 0.0746974087572229716869287586 10 0.0746974087572229716869287586 11 0.0746974087572229716869287586 12 0.0746974087572229716869287586 13 0.0000000000000000006443630462 * 14 0.0000000000000000006443630462 * 15 0.0000000000000000006443630462 * 16 0.0000000000000000006443630462 * 17 0.0014646459499707610053820250 * 18 0.0014646459499707610053820250 * 19 0.0014646459499707610053820250 * 20 0.0014646459499707610053820250 * 21 0.0025305704686156976768174331 * 22 0.0025305704686156976768174331 * 23 0.0025305704686156976768174331 * 24 0.0025305704686156976768174331 * 25 0.0000000000000000000008327933 * 26 0.0000000000000000000008327933 * 27 0.0000000000000000000008327933 * 28 0.0000000000000000000008327933 * 29 0.0000000001501921980136497106 * 30 0.0000000001501921980136497106 * 31 0.0000000001501921980136497106 * 32 0.0000000001501921980136497106 * [1] "\nGreenhouse-Geisser and Huynh-Feldt Corrections:" Effect GGe 9 DOMAIN 0.9894709 10 TEMPORAL_DO:DOMAIN 0.9894709 11 INTERVAL_DO:DOMAIN 0.9894709 12 TEMPORAL_DO:INTERVAL_DO:DOMAIN 0.9894709 13 INTERVAL 0.8630870 14 TEMPORAL_DO:INTERVAL 0.8630870 15 INTERVAL_DO:INTERVAL 0.8630870 16 TEMPORAL_DO:INTERVAL_DO:INTERVAL 0.8630870 17 TIME:DOMAIN 0.9741338 18 TEMPORAL_DO:TIME:DOMAIN 0.9741338 19 INTERVAL_DO:TIME:DOMAIN 0.9741338 20 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN 0.9741338 21 TIME:INTERVAL 0.9762236 22 TEMPORAL_DO:TIME:INTERVAL 0.9762236 23 INTERVAL_DO:TIME:INTERVAL 0.9762236 24 TEMPORAL_DO:INTERVAL_DO:TIME:INTERVAL 0.9762236 25 DOMAIN:INTERVAL 0.8875451 26 TEMPORAL_DO:DOMAIN:INTERVAL 0.8875451 27 INTERVAL_DO:DOMAIN:INTERVAL 0.8875451 28 TEMPORAL_DO:INTERVAL_DO:DOMAIN:INTERVAL 0.8875451 29 TIME:DOMAIN:INTERVAL 0.9371172 30 TEMPORAL_DO:TIME:DOMAIN:INTERVAL 0.9371172 31 INTERVAL_DO:TIME:DOMAIN:INTERVAL 0.9371172 32 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN:INTERVAL 0.9371172 p[GG] p[GG]<.05 9 0.00000000000000000000000000000000000878095702043403366407 * 10 0.53102721370755712193556519196135923266410827636718750000 11 0.96454613558369939330106035413336940109729766845703125000 12 0.36700584933971319712142644675623159855604171752929687500 13 0.00000000000000000000000000000000000000000000000001423011 * 14 0.94974047551632334585036687712999992072582244873046875000 15 0.47471969511650258244372935223509557545185089111328125000 16 0.62411323153516118367178933112882077693939208984375000000 17 0.64220700026879307120708517686580307781696319580078125000 18 0.38185330242177406567805064696585759520530700683593750000 19 0.52725524405891821544400954735465347766876220703125000000 20 0.43822405490061627775233432657842058688402175903320312500 21 0.00121306722426379781816507819058870154549367725849151611 * 22 0.00000000348498192042227194651846100548198137403232976794 * 23 0.92798416359171342904232915316242724657058715820312500000 24 0.50409969930842879470844764000503346323966979980468750000 25 0.00000008159469990521786758597144739724171813577413558960 * 26 0.56800731349628441613219820283120498061180114746093750000 27 0.84875678445067226363107693032361567020416259765625000000 28 0.51496197363380802336507713334867730736732482910156250000 29 0.34088544045227187062607754342025145888328552246093750000 30 0.45149296694178431277322260939399711787700653076171875000 31 0.28291991100553914861848170403391122817993164062500000000 32 0.57910295605858019829526028843247331678867340087890625000 HFe p[HF] 9 0.9934946 0.000000000000000000000000000000000006451264831904605766971 10 0.9934946 0.531649912402019864110513935884227976202964782714843750000 11 0.9934946 0.964943684916574118126675330131547525525093078613281250000 12 0.9934946 0.367263893712653555212455103173851966857910156250000000000 13 0.8658807 0.000000000000000000000000000000000000000000000000009983715 14 0.8658807 0.950140740323583976589816302293911576271057128906250000000 15 0.8658807 0.475152771510257476705874069011770188808441162109375000000 16 0.8658807 0.624766710949890224924274662043899297714233398437500000000 17 0.9780012 0.643000131912498607000827632873551920056343078613281250000 18 0.9780012 0.382143260850359378633100959632429294288158416748046875000 19 0.9780012 0.527860127804424372754965588683262467384338378906250000000 20 0.9780012 0.438641734987292086778154498460935428738594055175781250000 21 0.9801122 0.001193423570738182722811293601239412964787334203720092773 22 0.9801122 0.000000003271278107664685864605647047653746994910761713982 23 0.9801122 0.928577702594824749837698618648573756217956542968750000000 24 0.9801122 0.504659681866748810463718655228149145841598510742187500000 25 0.8948795 0.000000073184971201024083308286916071949690376641228795052 26 0.8948795 0.569122361981873936542797309812158346176147460937500000000 27 0.8948795 0.850266004147786302880263065162580460309982299804687500000 28 0.8948795 0.515867440527561615937202077475376427173614501953125000000 29 0.9453077 0.341009526697419074192652033161721192300319671630859375000 30 0.9453077 0.452137458526167157479846991918748244643211364746093750000 31 0.9453077 0.282785796339191430881498945382190868258476257324218750000 32 0.9453077 0.580300791673543203685881053388584405183792114257812500000 p[HF]<.05 9 * 10 11 12 13 * 14 15 16 17 18 19 20 21 * 22 * 23 24 25 * 26 27 28 29 30 31 32 [1] "\n=== CORRECTED DEGREES OF FREEDOM ===" Effect Original_DFn Original_DFd 1 DOMAIN 2 972 2 TEMPORAL_DO:DOMAIN 2 972 3 INTERVAL_DO:DOMAIN 2 972 4 TEMPORAL_DO:INTERVAL_DO:DOMAIN 2 972 5 INTERVAL 2 972 6 TEMPORAL_DO:INTERVAL 2 972 7 INTERVAL_DO:INTERVAL 2 972 8 TEMPORAL_DO:INTERVAL_DO:INTERVAL 2 972 9 TIME:DOMAIN 2 972 10 TEMPORAL_DO:TIME:DOMAIN 2 972 11 INTERVAL_DO:TIME:DOMAIN 2 972 12 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN 2 972 13 TIME:INTERVAL 2 972 14 TEMPORAL_DO:TIME:INTERVAL 2 972 15 INTERVAL_DO:TIME:INTERVAL 2 972 16 TEMPORAL_DO:INTERVAL_DO:TIME:INTERVAL 2 972 17 DOMAIN:INTERVAL 4 1944 18 TEMPORAL_DO:DOMAIN:INTERVAL 4 1944 19 INTERVAL_DO:DOMAIN:INTERVAL 4 1944 20 TEMPORAL_DO:INTERVAL_DO:DOMAIN:INTERVAL 4 1944 21 TIME:DOMAIN:INTERVAL 4 1944 22 TEMPORAL_DO:TIME:DOMAIN:INTERVAL 4 1944 23 INTERVAL_DO:TIME:DOMAIN:INTERVAL 4 1944 24 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN:INTERVAL 4 1944 GG_DFn GG_DFd HF_DFn HF_DFd GG_epsilon HF_epsilon 1 1.978942 961.7657 1.986989 965.6768 0.9894709 0.9934946 2 1.978942 961.7657 1.986989 965.6768 0.9894709 0.9934946 3 1.978942 961.7657 1.986989 965.6768 0.9894709 0.9934946 4 1.978942 961.7657 1.986989 965.6768 0.9894709 0.9934946 5 1.726174 838.9205 1.731761 841.6360 0.8630870 0.8658807 6 1.726174 838.9205 1.731761 841.6360 0.8630870 0.8658807 7 1.726174 838.9205 1.731761 841.6360 0.8630870 0.8658807 8 1.726174 838.9205 1.731761 841.6360 0.8630870 0.8658807 9 1.948268 946.8581 1.956002 950.6171 0.9741338 0.9780012 10 1.948268 946.8581 1.956002 950.6171 0.9741338 0.9780012 11 1.948268 946.8581 1.956002 950.6171 0.9741338 0.9780012 12 1.948268 946.8581 1.956002 950.6171 0.9741338 0.9780012 13 1.952447 948.8894 1.960224 952.6691 0.9762236 0.9801122 14 1.952447 948.8894 1.960224 952.6691 0.9762236 0.9801122 15 1.952447 948.8894 1.960224 952.6691 0.9762236 0.9801122 16 1.952447 948.8894 1.960224 952.6691 0.9762236 0.9801122 17 3.550180 1725.3877 3.579518 1739.6458 0.8875451 0.8948795 18 3.550180 1725.3877 3.579518 1739.6458 0.8875451 0.8948795 19 3.550180 1725.3877 3.579518 1739.6458 0.8875451 0.8948795 20 3.550180 1725.3877 3.579518 1739.6458 0.8875451 0.8948795 21 3.748469 1821.7559 3.781231 1837.6782 0.9371172 0.9453077 22 3.748469 1821.7559 3.781231 1837.6782 0.9371172 0.9453077 23 3.748469 1821.7559 3.781231 1837.6782 0.9371172 0.9453077 24 3.748469 1821.7559 3.781231 1837.6782 0.9371172 0.9453077 [1] "\n=== CORRECTED F-TESTS ===" [1] "\nBETWEEN-SUBJECTS EFFECTS:" [1] "TEMPORAL_DO: F(1, 486) = 0.007, p = 0.935166" [1] "INTERVAL_DO: F(1, 486) = 0.001, p = 0.976130" [1] "TEMPORAL_DO:INTERVAL_DO: F(1, 486) = 3.126, p = 0.077664" [1] "\nWITHIN-SUBJECTS EFFECTS:" [1] "TIME: F(1, 486) = 40.323, p = 0.000000 (2 levels, sphericity satisfied)" [1] "DOMAIN: F(2, 972) = 88.764, p = 0.000000" [1] "INTERVAL: F(2, 972) = 151.851, p = 0.000000" [1] "\nINTERACTIONS WITH SPHERICITY CORRECTIONS:" [1] "\nDOMAIN:" [1] " Original: F(2, 972) = 88.764" [1] " GG-corrected: F(1.98, 961.77) = 88.764, p = 0.000000" [1] " HF-corrected: F(1.99, 965.68) = 88.764, p = 0.000000" [1] "\nTEMPORAL_DO:DOMAIN:" [1] " Original: F(2, 972) = 0.630" [1] " GG-corrected: F(1.98, 961.77) = 0.630, p = 0.531027" [1] " HF-corrected: F(1.99, 965.68) = 0.630, p = 0.531650" [1] "\nINTERVAL_DO:DOMAIN:" [1] " Original: F(2, 972) = 0.035" [1] " GG-corrected: F(1.98, 961.77) = 0.035, p = 0.964546" [1] " HF-corrected: F(1.99, 965.68) = 0.035, p = 0.964944" [1] "\nTEMPORAL_DO:INTERVAL_DO:DOMAIN:" [1] " Original: F(2, 972) = 1.002" [1] " GG-corrected: F(1.98, 961.77) = 1.002, p = 0.367006" [1] " HF-corrected: F(1.99, 965.68) = 1.002, p = 0.367264" [1] "\nINTERVAL:" [1] " Original: F(2, 972) = 151.851" [1] " GG-corrected: F(1.73, 838.92) = 151.851, p = 0.000000" [1] " HF-corrected: F(1.73, 841.64) = 151.851, p = 0.000000" [1] "\nTEMPORAL_DO:INTERVAL:" [1] " Original: F(2, 972) = 0.035" [1] " GG-corrected: F(1.73, 838.92) = 0.035, p = 0.949740" [1] " HF-corrected: F(1.73, 841.64) = 0.035, p = 0.950141" [1] "\nINTERVAL_DO:INTERVAL:" [1] " Original: F(2, 972) = 0.705" [1] " GG-corrected: F(1.73, 838.92) = 0.705, p = 0.474720" [1] " HF-corrected: F(1.73, 841.64) = 0.705, p = 0.475153" [1] "\nTEMPORAL_DO:INTERVAL_DO:INTERVAL:" [1] " Original: F(2, 972) = 0.425" [1] " GG-corrected: F(1.73, 838.92) = 0.425, p = 0.624113" [1] " HF-corrected: F(1.73, 841.64) = 0.425, p = 0.624767" [1] "\nTIME:DOMAIN:" [1] " Original: F(2, 972) = 0.435" [1] " GG-corrected: F(1.95, 946.86) = 0.435, p = 0.642207" [1] " HF-corrected: F(1.96, 950.62) = 0.435, p = 0.643000" [1] "\nTEMPORAL_DO:TIME:DOMAIN:" [1] " Original: F(2, 972) = 0.959" [1] " GG-corrected: F(1.95, 946.86) = 0.959, p = 0.381853" [1] " HF-corrected: F(1.96, 950.62) = 0.959, p = 0.382143" [1] "\nINTERVAL_DO:TIME:DOMAIN:" [1] " Original: F(2, 972) = 0.633" [1] " GG-corrected: F(1.95, 946.86) = 0.633, p = 0.527255" [1] " HF-corrected: F(1.96, 950.62) = 0.633, p = 0.527860" [1] "\nTEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN:" [1] " Original: F(2, 972) = 0.819" [1] " GG-corrected: F(1.95, 946.86) = 0.819, p = 0.438224" [1] " HF-corrected: F(1.96, 950.62) = 0.819, p = 0.438642" [1] "\nTIME:INTERVAL:" [1] " Original: F(2, 972) = 6.862" [1] " GG-corrected: F(1.95, 948.89) = 6.862, p = 0.001213" [1] " HF-corrected: F(1.96, 952.67) = 6.862, p = 0.001193" [1] "\nTEMPORAL_DO:TIME:INTERVAL:" [1] " Original: F(2, 972) = 20.273" [1] " GG-corrected: F(1.95, 948.89) = 20.273, p = 0.000000" [1] " HF-corrected: F(1.96, 952.67) = 20.273, p = 0.000000" [1] "\nINTERVAL_DO:TIME:INTERVAL:" [1] " Original: F(2, 972) = 0.071" [1] " GG-corrected: F(1.95, 948.89) = 0.071, p = 0.927984" [1] " HF-corrected: F(1.96, 952.67) = 0.071, p = 0.928578" [1] "\nTEMPORAL_DO:INTERVAL_DO:TIME:INTERVAL:" [1] " Original: F(2, 972) = 0.679" [1] " GG-corrected: F(1.95, 948.89) = 0.679, p = 0.504100" [1] " HF-corrected: F(1.96, 952.67) = 0.679, p = 0.504660" [1] "\nDOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 10.651" [1] " GG-corrected: F(3.55, 1725.39) = 10.651, p = 0.000000" [1] " HF-corrected: F(3.58, 1739.65) = 10.651, p = 0.000000" [1] "\nTEMPORAL_DO:DOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 0.711" [1] " GG-corrected: F(3.55, 1725.39) = 0.711, p = 0.568007" [1] " HF-corrected: F(3.58, 1739.65) = 0.711, p = 0.569122" [1] "\nINTERVAL_DO:DOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 0.312" [1] " GG-corrected: F(3.55, 1725.39) = 0.312, p = 0.848757" [1] " HF-corrected: F(3.58, 1739.65) = 0.312, p = 0.850266" [1] "\nTEMPORAL_DO:INTERVAL_DO:DOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 0.795" [1] " GG-corrected: F(3.55, 1725.39) = 0.795, p = 0.514962" [1] " HF-corrected: F(3.58, 1739.65) = 0.795, p = 0.515867" [1] "\nTIME:DOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 1.127" [1] " GG-corrected: F(3.75, 1821.76) = 1.127, p = 0.340885" [1] " HF-corrected: F(3.78, 1837.68) = 1.127, p = 0.341010" [1] "\nTEMPORAL_DO:TIME:DOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 0.911" [1] " GG-corrected: F(3.75, 1821.76) = 0.911, p = 0.451493" [1] " HF-corrected: F(3.78, 1837.68) = 0.911, p = 0.452137" [1] "\nINTERVAL_DO:TIME:DOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 1.264" [1] " GG-corrected: F(3.75, 1821.76) = 1.264, p = 0.282920" [1] " HF-corrected: F(3.78, 1837.68) = 1.264, p = 0.282786" [1] "\nTEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN:INTERVAL:" [1] " Original: F(4, 1944) = 0.706" [1] " GG-corrected: F(3.75, 1821.76) = 0.706, p = 0.579103" [1] " HF-corrected: F(3.78, 1837.68) = 0.706, p = 0.580301" [1] "\n=== EFFECT SIZES (GENERALIZED ETA SQUARED) ===" [1] "Generalized Eta Squared:" Effect ges 1 (Intercept) 0.53236 2 TEMPORAL_DO 0.00001 3 INTERVAL_DO 0.00000 5 TIME 0.00736 9 DOMAIN 0.02520 13 INTERVAL 0.02311 4 TEMPORAL_DO:INTERVAL_DO 0.00267 6 TEMPORAL_DO:TIME 0.00024 7 INTERVAL_DO:TIME 0.00002 10 TEMPORAL_DO:DOMAIN 0.00018 11 INTERVAL_DO:DOMAIN 0.00001 14 TEMPORAL_DO:INTERVAL 0.00001 15 INTERVAL_DO:INTERVAL 0.00011 17 TIME:DOMAIN 0.00006 21 TIME:INTERVAL 0.00071 25 DOMAIN:INTERVAL 0.00183 8 TEMPORAL_DO:INTERVAL_DO:TIME 0.00008 12 TEMPORAL_DO:INTERVAL_DO:DOMAIN 0.00029 16 TEMPORAL_DO:INTERVAL_DO:INTERVAL 0.00007 18 TEMPORAL_DO:TIME:DOMAIN 0.00014 19 INTERVAL_DO:TIME:DOMAIN 0.00009 22 TEMPORAL_DO:TIME:INTERVAL 0.00209 23 INTERVAL_DO:TIME:INTERVAL 0.00001 26 TEMPORAL_DO:DOMAIN:INTERVAL 0.00012 27 INTERVAL_DO:DOMAIN:INTERVAL 0.00005 29 TIME:DOMAIN:INTERVAL 0.00017 20 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN 0.00012 24 TEMPORAL_DO:INTERVAL_DO:TIME:INTERVAL 0.00007 28 TEMPORAL_DO:INTERVAL_DO:DOMAIN:INTERVAL 0.00014 30 TEMPORAL_DO:TIME:DOMAIN:INTERVAL 0.00013 31 INTERVAL_DO:TIME:DOMAIN:INTERVAL 0.00019 32 TEMPORAL_DO:INTERVAL_DO:TIME:DOMAIN:INTERVAL 0.00010 [1] "\n=== POST-HOC COMPARISONS ===" [1] "Main Effect of TIME:" NOTE: Results may be misleading due to involvement in interactions [1] "Estimated Marginal Means:" TIME emmean SE df lower.CL upper.CL Past 0.768 0.0213 688 0.726 0.810 Future 0.653 0.0213 688 0.612 0.695 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, DOMAIN, INTERVAL Warning: EMMs are biased unless design is perfectly balanced Confidence level used: 0.95 [1] "\nPairwise Contrasts:" contrast estimate SE df t.ratio p.value Past - Future 0.114 0.018 486 6.350 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, DOMAIN, INTERVAL [1] "\nMain Effect of DOMAIN:" NOTE: Results may be misleading due to involvement in interactions [1] "Estimated Marginal Means:" DOMAIN emmean SE df lower.CL upper.CL Preferences 0.628 0.0224 829 0.584 0.672 Personality 0.861 0.0224 829 0.817 0.905 Values 0.643 0.0224 829 0.599 0.687 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME, INTERVAL Warning: EMMs are biased unless design is perfectly balanced Confidence level used: 0.95 [1] "\nPairwise Contrasts:" contrast estimate SE df t.ratio p.value Preferences - Personality -0.2335 0.0196 972 -11.912 <.0001 Preferences - Values -0.0154 0.0196 972 -0.788 1.0000 Personality - Values 0.2181 0.0196 972 11.125 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME, INTERVAL P value adjustment: bonferroni method for 3 tests [1] "\nMain Effect of INTERVAL:" NOTE: Results may be misleading due to involvement in interactions [1] "Estimated Marginal Means:" INTERVAL emmean SE df lower.CL upper.CL 5 0.729 0.021 670 0.688 0.770 10 0.825 0.021 670 0.784 0.867 5_10 0.578 0.021 670 0.536 0.619 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME, DOMAIN Warning: EMMs are biased unless design is perfectly balanced Confidence level used: 0.95 [1] "\nPairwise Contrasts:" contrast estimate SE df t.ratio p.value 5 - 10 -0.0966 0.0143 972 -6.735 <.0001 5 - 5_10 0.1513 0.0143 972 10.552 <.0001 10 - 5_10 0.2479 0.0143 972 17.287 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME, DOMAIN P value adjustment: bonferroni method for 3 tests [1] "\nMain Effect of TEMPORAL_DO:" NOTE: Results may be misleading due to involvement in interactions contrast estimate SE df t.ratio p.value 01PAST - 02FUT 0.00316 0.0388 486 0.081 0.9352 Results are averaged over the levels of: INTERVAL_DO, TIME, DOMAIN, INTERVAL [1] "\nMain Effect of INTERVAL_DO:" NOTE: Results may be misleading due to involvement in interactions contrast estimate SE df t.ratio p.value INTERVAL_DO5 - INTERVAL_DO10 0.00116 0.0388 486 0.030 0.9761 Results are averaged over the levels of: TEMPORAL_DO, TIME, DOMAIN, INTERVAL [1] "\n=== COHEN'S D FOR MAIN EFFECTS ===" [1] "\n=== COHEN'S D FOR TIME MAIN EFFECT ===" [1] "TIME main effect contrast:" contrast estimate SE df t.ratio p.value Past - Future 0.1142276 0.01798846 486 6.350 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, DOMAIN, INTERVAL [1] "\nCohen's d for TIME main effect:" [1] "Past vs Future: n1 = 4410, n2 = 4410" [1] "Cohen's d: 0.16649" [1] "Effect size interpretation: negligible" [1] "p-value: 0.00000" [1] "\n=== COHEN'S D FOR DOMAIN MAIN EFFECT ===" [1] "DOMAIN main effect contrasts:" contrast estimate SE df t.ratio p.value Preferences - Personality -0.23354947 0.01960542 972 -11.912 <.0001 Preferences - Values -0.01543953 0.01960542 972 -0.788 1.0000 Personality - Values 0.21810994 0.01960542 972 11.125 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME, INTERVAL P value adjustment: bonferroni method for 3 tests [1] "\nCohen's d for significant DOMAIN contrasts:" [1] "Comparison: Preferences - Personality" [1] " n1 = 2940, n2 = 2940" [1] " Cohen's d: -0.34313" [1] " Effect size interpretation: small" [1] " p-value: 0.00000" [1] "" [1] "Comparison: Personality - Values" [1] " n1 = 2940, n2 = 2940" [1] " Cohen's d: 0.31725" [1] " Effect size interpretation: small" [1] " p-value: 0.00000" [1] "" [1] "\n=== COHEN'S D FOR INTERVAL MAIN EFFECT ===" [1] "INTERVAL main effect contrasts:" contrast estimate SE df t.ratio p.value 5 - 10 -0.09657529 0.01433895 972 -6.735 <.0001 5 - 5_10 0.15130424 0.01433895 972 10.552 <.0001 10 - 5_10 0.24787953 0.01433895 972 17.287 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME, DOMAIN P value adjustment: bonferroni method for 3 tests [1] "\nCohen's d for significant INTERVAL contrasts:" [1] "Comparison: 5 - 10" [1] " n1 = 2940, n2 = 2940" [1] " Cohen's d: -0.13847" [1] " Effect size interpretation: negligible" [1] " p-value: 0.00000" [1] "" [1] "Comparison: 5 - 5_10" [1] " n1 = 2940, n2 = 2940" [1] " Cohen's d: 0.23269" [1] " Effect size interpretation: small" [1] " p-value: 0.00000" [1] "" [1] "Comparison: 10 - 5_10" [1] " n1 = 2940, n2 = 2940" [1] " Cohen's d: 0.36607" [1] " Effect size interpretation: small" [1] " p-value: 0.00000" [1] "" [1] "\n=== INTERACTION EXPLORATIONS ===" [1] "Significant interactions found:" Effect p 15 TIME:INTERVAL 0.001097858070070 16 DOMAIN:INTERVAL 0.000000015427828 22 TEMPORAL_DO:TIME:INTERVAL 0.000000002366928 [1] "\n=== TIME ├ù INTERVAL INTERACTION (SIGNIFICANT) ===" NOTE: Results may be misleading due to involvement in interactions [1] "Estimated Marginal Means:" TIME INTERVAL emmean SE df lower.CL upper.CL Past 5 0.762 0.0238 1053 0.716 0.809 Future 5 0.695 0.0238 1053 0.649 0.742 Past 10 0.888 0.0238 1053 0.841 0.934 Future 10 0.763 0.0238 1053 0.716 0.810 Past 5_10 0.653 0.0238 1053 0.607 0.700 Future 5_10 0.502 0.0238 1053 0.455 0.549 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, DOMAIN Warning: EMMs are biased unless design is perfectly balanced Confidence level used: 0.95 [1] "\nSimple Effects of INTERVAL within each TIME:" TIME = Past: contrast estimate SE df t.ratio p.value 5 - 10 -0.1254 0.0185 1867 -6.783 <.0001 5 - 5_10 0.1090 0.0185 1867 5.897 <.0001 10 - 5_10 0.2344 0.0185 1867 12.680 <.0001 TIME = Future: contrast estimate SE df t.ratio p.value 5 - 10 -0.0678 0.0185 1867 -3.666 0.0008 5 - 5_10 0.1936 0.0185 1867 10.474 <.0001 10 - 5_10 0.2614 0.0185 1867 14.140 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, DOMAIN P value adjustment: bonferroni method for 3 tests [1] "\nSimple Effects of TIME within each INTERVAL:" INTERVAL = 5: contrast estimate SE df t.ratio p.value Past - Future 0.0668 0.0225 1023 2.973 0.0030 INTERVAL = 10: contrast estimate SE df t.ratio p.value Past - Future 0.1244 0.0225 1023 5.538 <.0001 INTERVAL = 5_10: contrast estimate SE df t.ratio p.value Past - Future 0.1514 0.0225 1023 6.738 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, DOMAIN [1] "\n=== DOMAIN ├ù INTERVAL INTERACTION (SIGNIFICANT) ===" NOTE: Results may be misleading due to involvement in interactions [1] "Estimated Marginal Means:" DOMAIN INTERVAL emmean SE df lower.CL upper.CL Preferences 5 0.616 0.0254 1342 0.566 0.666 Personality 5 0.923 0.0254 1342 0.873 0.973 Values 5 0.647 0.0254 1342 0.597 0.697 Preferences 10 0.744 0.0254 1342 0.694 0.793 Personality 10 0.984 0.0254 1342 0.935 1.034 Values 10 0.748 0.0254 1342 0.699 0.798 Preferences 5_10 0.523 0.0254 1342 0.473 0.573 Personality 5_10 0.676 0.0254 1342 0.626 0.726 Values 5_10 0.534 0.0254 1342 0.484 0.583 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME Warning: EMMs are biased unless design is perfectly balanced Confidence level used: 0.95 [1] "\nSimple Effects of INTERVAL within each DOMAIN:" DOMAIN = Preferences: contrast estimate SE df t.ratio p.value 5 - 10 -0.1274 0.0208 2676 -6.122 <.0001 5 - 5_10 0.0930 0.0208 2676 4.466 <.0001 10 - 5_10 0.2204 0.0208 2676 10.587 <.0001 DOMAIN = Personality: contrast estimate SE df t.ratio p.value 5 - 10 -0.0611 0.0208 2676 -2.936 0.0101 5 - 5_10 0.2474 0.0208 2676 11.886 <.0001 10 - 5_10 0.3085 0.0208 2676 14.821 <.0001 DOMAIN = Values: contrast estimate SE df t.ratio p.value 5 - 10 -0.1012 0.0208 2676 -4.862 <.0001 5 - 5_10 0.1136 0.0208 2676 5.456 <.0001 10 - 5_10 0.2148 0.0208 2676 10.318 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME P value adjustment: bonferroni method for 3 tests [1] "\nSimple Effects of DOMAIN within each INTERVAL:" INTERVAL = 5: contrast estimate SE df t.ratio p.value Preferences - Personality -0.30714 0.0247 2097 -12.415 <.0001 Preferences - Values -0.03105 0.0247 2097 -1.255 0.6287 Personality - Values 0.27608 0.0247 2097 11.160 <.0001 INTERVAL = 10: contrast estimate SE df t.ratio p.value Preferences - Personality -0.24082 0.0247 2097 -9.734 <.0001 Preferences - Values -0.00483 0.0247 2097 -0.195 1.0000 Personality - Values 0.23599 0.0247 2097 9.539 <.0001 INTERVAL = 5_10: contrast estimate SE df t.ratio p.value Preferences - Personality -0.15269 0.0247 2097 -6.172 <.0001 Preferences - Values -0.01044 0.0247 2097 -0.422 1.0000 Personality - Values 0.14226 0.0247 2097 5.750 <.0001 Results are averaged over the levels of: TEMPORAL_DO, INTERVAL_DO, TIME P value adjustment: bonferroni method for 3 tests [1] "\n=== ANALYSIS COMPLETE ===" [1] "Mixed ANOVA analysis with three within-subjects factors (TIME, DOMAIN, INTERVAL)" [1] "and two between-subjects factors (TEMPORAL_DO, INTERVAL_DO) completed." [1] "Check the results above for significant effects and perform additional" [1] "interaction analyses as needed based on the significance patterns."