Rscript : ΓöÇΓöÇ Attaching core tidyverse packages 

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At C:\\Users\\irina\\AppData\\Local\\Temp\\ps-script-1e88d1ff-8e66-4d9a-90cf-0f9caea5137a.ps1:7 char:47

\+ ... OHI\\eohi1"; Rscript "mixed anova - DGEN.r" > "results - exp1 - mixed  ...

\+                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

&nbsp;   + CategoryInfo          : NotSpecified: (ΓöÇΓöÇ Attachin...se 2.0.0 ΓöÇΓöÇ:String) \[], RemoteException

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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 ΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇ

ΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇΓöÇ tidyverse\_conflicts() ΓöÇΓöÇ

Γ£û dplyr::filter() masks stats::filter()

Γ£û dplyr::lag()    masks stats::lag()

Γä╣ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Loading required package: carData



Attaching package: 'car'



The following object is masked from 'package:dplyr':



&nbsp;   recode



The following object is masked from 'package:purrr':



&nbsp;   some



Loading required package: lme4

Loading required package: Matrix



Attaching package: 'Matrix'



The following objects are masked from 'package:tidyr':



&nbsp;   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':



&nbsp;   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':

&nbsp; method                           from      

&nbsp; display.parameters\_distribution  datawizard

&nbsp; plot.parameters\_distribution     datawizard

&nbsp; print\_md.parameters\_distribution datawizard

\[1] "Dataset dimensions: 1063 x689"

\[1] "Number of participants: 1063"

\[1] "All required DGEN variables found!"

\[1] "Long data dimensions: 8504 x6"

\[1] "Number of participants: 1063"

\[1] "Descriptive statistics by TIME and DOMAIN:"

\# A tibble: 8 ├ù 11

&nbsp; TIME   DOMAIN          n  mean variance    sd median    q1    q3   min   max

&nbsp; <fct>  <fct>       <int> <dbl>    <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl>

1 Past   Preferences  1063  4.45     8.17  2.86      5     2     7     0    10

2 Past   Personality  1063  4.67     8.12  2.85      5     2     7     0    10

3 Past   Values       1063  4.41     8.50  2.91      4     2     7     0    10

4 Past   Life         1063  5.46     8.02  2.83      6     3     8     0    10

5 Future Preferences  1063  4.14     7.97  2.82      4     2     6     0    10

6 Future Personality  1063  4.23     7.92  2.81      4     2     6     0    10

7 Future Values       1063  3.92     7.94  2.82      3     2     6     0    10

8 Future Life         1063  5.05     8.11  2.85      5     3     7     0    10

\[1] "Descriptive statistics by TEMPORAL\_DO, TIME, and DOMAIN:"

\# A tibble: 16 ├ù 7

&nbsp;  TEMPORAL\_DO TIME   DOMAIN          n  mean variance    sd

&nbsp;  <fct>       <fct>  <fct>       <int> <dbl>    <dbl> <dbl>

&nbsp;1 01PAST      Past   Preferences   536  4.52     8.58  2.93

&nbsp;2 01PAST      Past   Personality   536  4.79     8.18  2.86

&nbsp;3 01PAST      Past   Values        536  4.49     8.35  2.89

&nbsp;4 01PAST      Past   Life          536  5.73     7.71  2.78

&nbsp;5 01PAST      Future Preferences   536  4.16     8.16  2.86

&nbsp;6 01PAST      Future Personality   536  4.32     8.00  2.83

&nbsp;7 01PAST      Future Values        536  4.01     8.04  2.84

&nbsp;8 01PAST      Future Life          536  5.20     8.21  2.87

&nbsp;9 02FUT       Past   Preferences   527  4.39     7.76  2.79

10 02FUT       Past   Personality   527  4.55     8.04  2.84

11 02FUT       Past   Values        527  4.34     8.65  2.94

12 02FUT       Past   Life          527  5.19     8.20  2.86

13 02FUT       Future Preferences   527  4.13     7.79  2.79

14 02FUT       Future Personality   527  4.14     7.83  2.80

15 02FUT       Future Values        527  3.83     7.84  2.80

16 02FUT       Future Life          527  4.90     7.97  2.82

\[1] "Data after removing missing values: 8504 x6"

\[1] "Missing values by TIME and DOMAIN:"

\# A tibble: 8 ├ù 5

&nbsp; TIME   DOMAIN      n\_total n\_missing pct\_missing

&nbsp; <fct>  <fct>         <int>     <int>       <dbl>

1 Past   Preferences    1063         0           0

2 Past   Personality    1063         0           0

3 Past   Values         1063         0           0

4 Past   Life           1063         0           0

5 Future Preferences    1063         0           0

6 Future Personality    1063         0           0

7 Future Values         1063         0           0

8 Future Life           1063         0           0

\[1] "Outlier summary (IQR method):"

\# A tibble: 8 ├ù 11

&nbsp; TIME   DOMAIN          n  mean    sd    q1    q3   iqr lower\_bound upper\_bound

&nbsp; <fct>  <fct>       <int> <dbl> <dbl> <dbl> <dbl> <dbl>       <dbl>       <dbl>

1 Past   Preferences  1063  4.45  2.86     2     7     5        -5.5        14.5

2 Past   Personality  1063  4.67  2.85     2     7     5        -5.5        14.5

3 Past   Values       1063  4.41  2.91     2     7     5        -5.5        14.5

4 Past   Life         1063  5.46  2.83     3     8     5        -4.5        15.5

5 Future Preferences  1063  4.14  2.82     2     6     4        -4          12  

6 Future Personality  1063  4.23  2.81     2     6     4        -4          12  

7 Future Values       1063  3.92  2.82     2     6     4        -4          12  

8 Future Life         1063  5.05  2.85     3     7     4        -3          13  

\# Γä╣ 1 more variable: n\_outliers <int>

\[1] "Anderson-Darling normality test results:"

\# A tibble: 8 ├ù 5

&nbsp; TIME   DOMAIN          n ad\_statistic ad\_p\_value

&nbsp; <fct>  <fct>       <dbl>        <dbl>      <dbl>

1 Past   Preferences  1063         13.8          0

2 Past   Personality  1063         13.6          0

3 Past   Values       1063         16.3          0

4 Past   Life         1063         13.0          0

5 Future Preferences  1063         17.4          0

6 Future Personality  1063         16.9          0

7 Future Values       1063         21.7          0

8 Future Life         1063         12.1          0

\[1] "Homogeneity of variance across TIME within each DOMAIN:"

\# A tibble: 4 ├ù 3

&nbsp; DOMAIN      levene\_F levene\_p

&nbsp; <fct>          <dbl>    <dbl>

1 Preferences   0.115     0.735

2 Personality   0.0390    0.843

3 Values        1.50      0.221

4 Life          0.453     0.501

\[1] "Homogeneity of variance across DOMAIN within each TIME:"

\# A tibble: 2 ├ù 3

&nbsp; TIME   levene\_F levene\_p

&nbsp; <fct>     <dbl>    <dbl>

1 Past      1.43     0.233

2 Future    0.818    0.484

\[1] "=== CHECKING TEMPORAL\_DO VALUES ==="

\[1] "Unique TEMPORAL\_DO values:"

\[1] 01PAST 02FUT 

Levels: 01PAST 02FUT

\[1] "TEMPORAL\_DO value counts:"



01PAST  02FUT 

&nbsp; 4288   4216 

\[1] "\\n=== OBSERVED F-MAX RATIOS: TEMPORAL\_DO within each TIME ├ù DOMAIN combination ==="

\# A tibble: 8 ├ù 5

&nbsp; TIME   DOMAIN      past\_var fut\_var f\_max\_ratio

&nbsp; <fct>  <fct>          <dbl>   <dbl>       <dbl>

1 Past   Preferences     8.58    7.76        1.11

2 Past   Personality     8.18    8.04        1.02

3 Past   Values          8.35    8.65        1.04

4 Past   Life            7.71    8.20        1.06

5 Future Preferences     8.16    7.79        1.05

6 Future Personality     8.00    7.83        1.02

7 Future Values          8.04    7.84        1.03

8 Future Life            8.21    7.97        1.03

\[1] "\\n=== HARTLEY'S F-MAX TEST RESULTS ==="

\# A tibble: 8 ├ù 5

&nbsp; TIME   DOMAIN      observed\_ratio critical\_95 significant

&nbsp; <fct>  <fct>                <dbl>       <dbl> <lgl>      

1 Past   Preferences           1.11        1.23 FALSE      

2 Past   Personality           1.02        1.12 FALSE      

3 Past   Values                1.04        1.14 FALSE      

4 Past   Life                  1.06        1.18 FALSE      

5 Future Preferences           1.05        1.17 FALSE      

6 Future Personality           1.02        1.15 FALSE      

7 Future Values                1.03        1.15 FALSE      

8 Future Life                  1.03        1.15 FALSE      

\[1] "Data size for ANOVA: 8504 rows"

\[1] "Number of participants: 1063"

\[1] "Design factors: TIME (2), DOMAIN (4), TEMPORAL\_DO (2)"

\[1] "Complete cases: 8504 out of 8504"

\[1] "Design is balanced: each participant has data for all TIME ├ù DOMAIN 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:"

&nbsp;                  Effect DFn  DFd           SSn       SSd            F

1             (Intercept)   1 1061 175403.313893 45334.099 4105.1420831

2             TEMPORAL\_DO   1 1061    104.781437 45334.099    2.4523065

**3                    TIME   1 1061    363.139680  5710.697   67.4683362**

**4                  DOMAIN   3 3183   1524.702983 10462.463  154.6203659**

5        TEMPORAL\_DO:TIME   1 1061      4.340056  5710.697    0.8063464

**6      TEMPORAL\_DO:DOMAIN   3 3183     33.288120 10462.463    3.3757534**

7             TIME:DOMAIN   3 3183      9.191110  7100.516    1.3733886

8 TEMPORAL\_DO:TIME:DOMAIN   3 3183      4.974741  7100.516    0.7433545

&nbsp;                                                                                                    p

1 0.00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000

2 0.11765050104906209227362268165961722843348979949951171875000000000000000000000000000000000000000000

3 0.00000000000000061782799119098067114168315594469049756298772990703582763671875000000000000000000000

4 0.00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000150209

5 0.36940636618506739186074128156178630888462066650390625000000000000000000000000000000000000000000000

6 0.01763146579785550976948726997761696111410856246948242187500000000000000000000000000000000000000000

7 0.24898565439172731794670312410744372755289077758789062500000000000000000000000000000000000000000000

8 0.52613525007520434151331301109166815876960754394531250000000000000000000000000000000000000000000000

&nbsp; p<.05           ges

1     \* 0.71883337333

2       0.00152492417

**3     \* 0.00526511333**

**4     \* 0.02174032681**

5       0.00006325496

**6     \* 0.00048495927**

7       0.00013394807

8       0.00007250462

\[1] "\\nMauchly's Test of Sphericity:"

&nbsp;                  Effect         W                                      p

5                  DOMAIN 0.8712463 0.000000000000000000000000000009197155

6      TEMPORAL\_DO:DOMAIN 0.8712463 0.000000000000000000000000000009197155

7             TIME:DOMAIN 0.9366421 0.000000000000139056847839002402420980

8 TEMPORAL\_DO:TIME:DOMAIN 0.9366421 0.000000000000139056847839002402420980

&nbsp; p<.05

5     \*

6     \*

7     \*

8     \*

**\[1] "\\nGreenhouse-Geisser and Huynh-Feldt Corrections:"**

                   **Effect       GGe**

**5                  DOMAIN 0.9120175**

**6      TEMPORAL\_DO:DOMAIN 0.9120175**

7             TIME:DOMAIN 0.9556034

8 TEMPORAL\_DO:TIME:DOMAIN 0.9556034

&nbsp;                                                                                         p\[GG]

5 0.0000000000000000000000000000000000000000000000000000000000000000000000000000000000001345237

6 0.0210110642827151770928306717678424320183694362640380859375000000000000000000000000000000000

7 0.2499237624236494703655608873305027373135089874267578125000000000000000000000000000000000000

8 0.5204622528563578320870419702259823679924011230468750000000000000000000000000000000000000000

&nbsp; p\[GG]<.05       HFe

**5         \* 0.9146073**

**6         \* 0.9146073**

7           0.9584655

8           0.9584655

&nbsp;                                                                                          p\[HF]

5 0.00000000000000000000000000000000000000000000000000000000000000000000000000000000000007847038

6 0.02090266902721321304325918788435956230387091636657714843750000000000000000000000000000000000

7 0.24986536855461360939756332300021313130855560302734375000000000000000000000000000000000000000

8 0.52083559605373963563579309266060590744018554687500000000000000000000000000000000000000000000

&nbsp; p\[HF]<.05

5         \*

6         \*

7          

8          



=== CORRECTED DEGREES OF FREEDOM ===

                   **Effect Original\_DFn Original\_DFd   GG\_DFn   GG\_DFd   HF\_DFn**

**1                  DOMAIN            3         3183 2.736053 2902.952 2.743822**

**2      TEMPORAL\_DO:DOMAIN            3         3183 2.736053 2902.952 2.743822**

3             TIME:DOMAIN            3         3183 2.866810 3041.686 2.875396

4 TEMPORAL\_DO:TIME:DOMAIN            3         3183 2.866810 3041.686 2.875396

    **HF\_DFd GG\_epsilon HF\_epsilon**

**1 2911.195  0.9120175  0.9146073**

**2 2911.195  0.9120175  0.9146073**

3 3050.796  0.9556034  0.9584655

4 3050.796  0.9556034  0.9584655



=== CORRECTED F-TESTS ===



**DOMAIN:**

  **Original: F(3, 3183) = 154.620**

  **GG-corrected: F(2.74, 2902.95) = 154.620, p = 0.000000**

  **HF-corrected: F(2.74, 2911.20) = 154.620, p = 0.000000**



**TEMPORAL\_DO:DOMAIN:**

  **Original: F(3, 3183) = 3.376**

  **GG-corrected: F(2.74, 2902.95) = 3.376, p = 0.021011**

  **HF-corrected: F(2.74, 2911.20) = 3.376, p = 0.020903**



TIME:DOMAIN:

&nbsp; Original: F(3, 3183) = 1.373

&nbsp; GG-corrected: F(2.87, 3041.69) = 1.373, p = 0.249924

&nbsp; HF-corrected: F(2.88, 3050.80) = 1.373, p = 0.249865



TEMPORAL\_DO:TIME:DOMAIN:

&nbsp; Original: F(3, 3183) = 0.743

&nbsp; GG-corrected: F(2.87, 3041.69) = 0.743, p = 0.520462

&nbsp; HF-corrected: F(2.88, 3050.80) = 0.743, p = 0.520836

\[1] "\\n=== EFFECT SIZES (GENERALIZED ETA SQUARED) ==="

\[1] "Generalized Eta Squared:"

&nbsp;                  Effect     ges

1             (Intercept) 0.71883

2             TEMPORAL\_DO 0.00152

**3                    TIME 0.00527**

**5                  DOMAIN 0.02174**

4        TEMPORAL\_DO:TIME 0.00006

**6      TEMPORAL\_DO:DOMAIN 0.00048**

7             TIME:DOMAIN 0.00013

8 TEMPORAL\_DO:TIME:DOMAIN 0.00007

\[1] "\\n=== POST-HOC COMPARISONS ==="

**\[1] "Main Effect of TIME:"**

NOTE: Results may be misleading due to involvement in interactions

\[1] "Estimated Marginal Means:"

&nbsp;TIME   emmean     SE   df lower.CL upper.CL

&nbsp;Past     4.75 0.0752 1324     4.60     4.90

&nbsp;Future   4.34 0.0752 1324     4.19     4.48



Results are averaged over the levels of: TEMPORAL\_DO, 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**

 **Past - Future    0.413 0.0503 1061   8.214  <.0001**



Results are averaged over the levels of: TEMPORAL\_DO, DOMAIN 

**\[1] "\\nMain Effect of DOMAIN:"**

NOTE: Results may be misleading due to involvement in interactions

\[1] "Estimated Marginal Means:"

&nbsp;DOMAIN      emmean     SE   df lower.CL upper.CL

&nbsp;Preferences   4.30 0.0786 1579     4.14     4.45

&nbsp;Personality   4.45 0.0786 1579     4.30     4.61

&nbsp;Values        4.17 0.0786 1579     4.01     4.32

&nbsp;Life          5.26 0.0786 1579     5.10     5.41



Results are averaged over the levels of: TEMPORAL\_DO, TIME 

Warning: EMMs are biased unless design is perfectly balanced 

Confidence level used: 0.95 

\[1] "\\nPairwise Contrasts:"

&nbsp;contrast                  estimate     SE   df t.ratio p.value

 **Preferences - Personality   -0.153 0.0556 3183  -2.747  0.0362**

&nbsp;Preferences - Values         0.132 0.0556 3183   2.375  0.1057

 **Preferences - Life          -0.957 0.0556 3183 -17.204  <.0001**

 **Personality - Values         0.285 0.0556 3183   5.122  <.0001**

 **Personality - Life          -0.804 0.0556 3183 -14.456  <.0001**

 **Values - Life               -1.089 0.0556 3183 -19.579  <.0001**



Results are averaged over the levels of: TEMPORAL\_DO, TIME 

P value adjustment: bonferroni method for 6 tests 

\[1] "\\nMain Effect of TEMPORAL\_DO:"

NOTE: Results may be misleading due to involvement in interactions

&nbsp;contrast       estimate    SE   df t.ratio p.value

&nbsp;01PAST - 02FUT    0.222 0.142 1061   1.566  0.1177



Results are averaged over the levels of: TIME, DOMAIN 

\[1] "\\n=== TEMPORAL\_DO ├ù TIME INTERACTION ==="

NOTE: Results may be misleading due to involvement in interactions

\[1] "Estimated Marginal Means:"

&nbsp;TEMPORAL\_DO TIME   emmean    SE   df lower.CL upper.CL

&nbsp;01PAST      Past     4.88 0.106 1322     4.67     5.09

&nbsp;02FUT       Past     4.62 0.106 1326     4.41     4.82

&nbsp;01PAST      Future   4.42 0.106 1322     4.22     4.63

&nbsp;02FUT       Future   4.25 0.106 1326     4.04     4.46



Results are averaged over the levels of: DOMAIN 

Warning: EMMs are biased unless design is perfectly balanced 

Confidence level used: 0.95 

\[1] "\\**nSimple Effects of TIME within each TEMPORAL\_DO:**"

**TEMPORAL\_DO = 01PAST:**

 **contrast      estimate     SE   df t.ratio p.value**

 **Past - Future    0.458 0.0709 1061   6.471  <.0001**



**TEMPORAL\_DO = 02FUT:**

 **contrast      estimate     SE   df t.ratio p.value**

 **Past - Future    0.368 0.0715 1061   5.151  <.0001**



Results are averaged over the levels of: DOMAIN 

\[1] "\\nSimple Effects of TEMPORAL\_DO within each TIME:"

TIME = Past:

&nbsp;contrast       estimate   SE   df t.ratio p.value

&nbsp;01PAST - 02FUT    0.267 0.15 1324   1.776  0.0759



TIME = Future:

&nbsp;contrast       estimate   SE   df t.ratio p.value

&nbsp;01PAST - 02FUT    0.177 0.15 1324   1.175  0.2400



Results are averaged over the levels of: DOMAIN 

\[1] "\\n=== **TIME ├ù DOMAIN INTERACTION** ==="

NOTE: Results may be misleading due to involvement in interactions

\[1] "Estimated Marginal Means:"

&nbsp;TIME   DOMAIN      emmean     SE   df lower.CL upper.CL

&nbsp;Past   Preferences   4.45 0.0872 2333     4.28     4.62

&nbsp;Future Preferences   4.14 0.0872 2333     3.97     4.31

&nbsp;Past   Personality   4.67 0.0872 2333     4.50     4.84

&nbsp;Future Personality   4.23 0.0872 2333     4.06     4.40

&nbsp;Past   Values        4.41 0.0872 2333     4.24     4.58

&nbsp;Future Values        3.92 0.0872 2333     3.75     4.09

&nbsp;Past   Life          5.46 0.0872 2333     5.29     5.63

&nbsp;Future Life          5.05 0.0872 2333     4.88     5.22



Results are averaged over the levels of: TEMPORAL\_DO 

Warning: EMMs are biased unless design is perfectly balanced 

Confidence level used: 0.95 

\[1] "\\nSimple Effects of DOMAIN within each TIME:"

TIME = Past:

&nbsp;contrast                  estimate    SE   df t.ratio p.value

&nbsp;Preferences - Personality  -0.2187 0.072 6141  -3.036  0.0145

&nbsp;Preferences - Values        0.0424 0.072 6141   0.588  1.0000

&nbsp;Preferences - Life         -1.0058 0.072 6141 -13.960  <.0001

&nbsp;Personality - Values        0.2611 0.072 6141   3.624  0.0018

&nbsp;Personality - Life         -0.7871 0.072 6141 -10.924  <.0001

&nbsp;Values - Life              -1.0482 0.072 6141 -14.549  <.0001



TIME = Future:

&nbsp;contrast                  estimate    SE   df t.ratio p.value

&nbsp;Preferences - Personality  -0.0868 0.072 6141  -1.205  1.0000

&nbsp;Preferences - Values        0.2217 0.072 6141   3.078  0.0126

&nbsp;Preferences - Life         -0.9076 0.072 6141 -12.597  <.0001

&nbsp;Personality - Values        0.3086 0.072 6141   4.283  0.0001

&nbsp;Personality - Life         -0.8207 0.072 6141 -11.391  <.0001

&nbsp;Values - Life              -1.1293 0.072 6141 -15.674  <.0001



Results are averaged over the levels of: TEMPORAL\_DO 

P value adjustment: bonferroni method for 6 tests 

**\[1] "\\nSimple Effects of TIME within each DOMAIN:"**

**DOMAIN = Preferences:**

 **contrast      estimate     SE   df t.ratio p.value**

 **Past - Future    0.311 0.0754 3524   4.126  <.0001**



**DOMAIN = Personality:**

 **contrast      estimate     SE   df t.ratio p.value**

 **Past - Future    0.443 0.0754 3524   5.875  <.0001**



**DOMAIN = Values:**

 **contrast      estimate     SE   df t.ratio p.value**

 **Past - Future    0.490 0.0754 3524   6.506  <.0001**



**DOMAIN = Life:**

 **contrast      estimate     SE   df t.ratio p.value**

 **Past - Future    0.409 0.0754 3524   5.429  <.0001**



Results are averaged over the levels of: TEMPORAL\_DO 

\[1] "\\n=== TEMPORAL\_DO ├ù DOMAIN INTERACTION ==="

NOTE: Results may be misleading due to involvement in interactions

\[1] "Estimated Marginal Means:"

&nbsp;TEMPORAL\_DO DOMAIN      emmean    SE   df lower.CL upper.CL

&nbsp;01PAST      Preferences   4.34 0.111 1575     4.12     4.56

&nbsp;02FUT       Preferences   4.26 0.111 1584     4.04     4.48

&nbsp;01PAST      Personality   4.56 0.111 1575     4.34     4.78

&nbsp;02FUT       Personality   4.34 0.111 1584     4.13     4.56

&nbsp;01PAST      Values        4.25 0.111 1575     4.03     4.47

&nbsp;02FUT       Values        4.08 0.111 1584     3.86     4.30

&nbsp;01PAST      Life          5.47 0.111 1575     5.25     5.68

&nbsp;02FUT       Life          5.04 0.111 1584     4.83     5.26



Results are averaged over the levels of: TIME 

Warning: EMMs are biased unless design is perfectly balanced 

Confidence level used: 0.95 

\[1] "\\nSimple Effects of DOMAIN within each TEMPORAL\_DO:"

TEMPORAL\_DO = 01PAST:

&nbsp;contrast                  estimate     SE   df t.ratio p.value

&nbsp;Preferences - Personality  -0.2183 0.0783 3183  -2.787  0.0321

&nbsp;Preferences - Values        0.0886 0.0783 3183   1.132  1.0000

&nbsp;Preferences - Life         -1.1269 0.0783 3183 -14.390  <.0001

&nbsp;Personality - Values        0.3069 0.0783 3183   3.919  0.0005

&nbsp;Personality - Life         -0.9086 0.0783 3183 -11.602  <.0001

&nbsp;Values - Life              -1.2155 0.0783 3183 -15.521  <.0001



TEMPORAL\_DO = 02FUT:

&nbsp;contrast                  estimate     SE   df t.ratio p.value

&nbsp;Preferences - Personality  -0.0873 0.0790 3183  -1.105  1.0000

&nbsp;Preferences - Values        0.1755 0.0790 3183   2.222  0.1579

&nbsp;Preferences - Life         -0.7865 0.0790 3183  -9.959  <.0001

&nbsp;Personality - Values        0.2628 0.0790 3183   3.328  0.0053

&nbsp;Personality - Life         -0.6992 0.0790 3183  -8.854  <.0001

&nbsp;Values - Life              -0.9620 0.0790 3183 -12.182  <.0001



Results are averaged over the levels of: TIME 

P value adjustment: bonferroni method for 6 tests 

\[1] "\\nSimple Effects of TEMPORAL\_DO within each DOMAIN:"

DOMAIN = Preferences:

&nbsp;contrast       estimate    SE   df t.ratio p.value

&nbsp;01PAST - 02FUT   0.0825 0.157 1579   0.524  0.6002



DOMAIN = Personality:

&nbsp;contrast       estimate    SE   df t.ratio p.value

&nbsp;01PAST - 02FUT   0.2134 0.157 1579   1.357  0.1749



DOMAIN = Values:

&nbsp;contrast       estimate    SE   df t.ratio p.value

&nbsp;01PAST - 02FUT   0.1694 0.157 1579   1.077  0.2818



DOMAIN = Life:

&nbsp;contrast       estimate    SE   df t.ratio p.value

&nbsp;01PAST - 02FUT   0.4228 0.157 1579   2.688  0.0073



Results are averaged over the levels of: TIME 

\[1] "\\n=== THREE-WAY INTERACTION ANALYSIS ==="

\[1] "Estimated Marginal Means:"

&nbsp;TEMPORAL\_DO TIME   DOMAIN      emmean    SE   df lower.CL upper.CL

&nbsp;01PAST      Past   Preferences   4.52 0.123 2321     4.28     4.76

&nbsp;02FUT       Past   Preferences   4.39 0.123 2344     4.14     4.63

&nbsp;01PAST      Future Preferences   4.16 0.123 2321     3.92     4.40

&nbsp;02FUT       Future Preferences   4.13 0.123 2344     3.89     4.37

&nbsp;01PAST      Past   Personality   4.80 0.123 2321     4.55     5.04

&nbsp;02FUT       Past   Personality   4.55 0.123 2344     4.31     4.79

&nbsp;01PAST      Future Personality   4.32 0.123 2321     4.08     4.56

&nbsp;02FUT       Future Personality   4.14 0.123 2344     3.90     4.38

&nbsp;01PAST      Past   Values        4.49 0.123 2321     4.24     4.73

&nbsp;02FUT       Past   Values        4.34 0.123 2344     4.09     4.58

&nbsp;01PAST      Future Values        4.02 0.123 2321     3.77     4.26

&nbsp;02FUT       Future Values        3.83 0.123 2344     3.58     4.07

&nbsp;01PAST      Past   Life          5.73 0.123 2321     5.49     5.97

&nbsp;02FUT       Past   Life          5.19 0.123 2344     4.95     5.43

&nbsp;01PAST      Future Life          5.20 0.123 2321     4.96     5.45

&nbsp;02FUT       Future Life          4.90 0.123 2344     4.65     5.14



Warning: EMMs are biased unless design is perfectly balanced 

Confidence level used: 0.95 

\[1] "\\nSimple Effects of TIME within each TEMPORAL\_DO ├ù DOMAIN combination:"

TEMPORAL\_DO = 01PAST, DOMAIN = Preferences:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.364 0.106 3524   3.428  0.0006



TEMPORAL\_DO = 02FUT, DOMAIN = Preferences:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.258 0.107 3524   2.411  0.0160



TEMPORAL\_DO = 01PAST, DOMAIN = Personality:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.476 0.106 3524   4.483  <.0001



TEMPORAL\_DO = 02FUT, DOMAIN = Personality:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.410 0.107 3524   3.829  0.0001



TEMPORAL\_DO = 01PAST, DOMAIN = Values:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.470 0.106 3524   4.430  <.0001



TEMPORAL\_DO = 02FUT, DOMAIN = Values:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.510 0.107 3524   4.769  <.0001



TEMPORAL\_DO = 01PAST, DOMAIN = Life:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.524 0.106 3524   4.940  <.0001



TEMPORAL\_DO = 02FUT, DOMAIN = Life:

&nbsp;contrast      estimate    SE   df t.ratio p.value

&nbsp;Past - Future    0.294 0.107 3524   2.748  0.0060



\[1] "\\n=== COHEN'S D FOR SIGNIFICANT TWO-WAY INTERACTIONS ==="

\[1] "\\n=== COHEN'S D FOR T**EMPORAL\_DO ├ù TIME INTERACTION** ==="

Significant pairwise comparisons (p < 0.05):

 **contrast      TEMPORAL\_DO  estimate         SE   df t.ratio p.value**

 **Past - Future 01PAST      0.4584888 0.07085809 1061   6.471  <.0001**

 **Past - Future 02FUT       0.3681214 0.07146058 1061   5.151  <.0001**



Results are averaged over the levels of: DOMAIN 



Cohen's d calculated from raw data:

**Comparison: Past - Future | 01PAST**

&nbsp; n1 = 2144, n2 = 2144

  **Cohen's d: 0.15841**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00000



**Comparison: Past - Future | 02FUT**

&nbsp; n1 = 2108, n2 = 2108

  **Cohen's d: 0.12907**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00000



No significant pairwise comparisons found.

\[1] "\\n=== **COHEN'S D FOR TIME ├ù DOMAI**N INTERACTION ==="

Significant pairwise comparisons (p < 0.05):

 **contrast      DOMAIN       estimate         SE      df t.ratio p.value**

 **Past - Future Preferences 0.3109352 0.07536529 3523.81   4.126  <.0001**

 **Past - Future Personality 0.4428067 0.07536529 3523.81   5.875  <.0001**

 **Past - Future Values      0.4902928 0.07536529 3523.81   6.506  <.0001**

 **Past - Future Life        0.4091857 0.07536529 3523.81   5.429  <.0001**



Results are averaged over the levels of: TEMPORAL\_DO 



Cohen's d calculated from raw data:

**Comparison: Past - Future | Preferences**

&nbsp; n1 = 1063, n2 = 1063

  **Cohen's d: 0.10962**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00004



**Comparison: Past - Future | Personality**

&nbsp; n1 = 1063, n2 = 1063

&nbsp; **Cohen's d: 0.15646**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00000



**Comparison: Past - Future | Values**

&nbsp; n1 = 1063, n2 = 1063

  **Cohen's d: 0.17095**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00000



**Comparison: Past - Future | Life**

&nbsp; n1 = 1063, n2 = 1063

  **Cohen's d: 0.14446**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00000



Significant pairwise comparisons (p < 0.05):

&nbsp;contrast                  TIME     estimate         SE      df t.ratio p.value

&nbsp;Preferences - Personality Past   -0.2187208 0.07204929 6140.98  -3.036  0.0145

&nbsp;Preferences - Life        Past   -1.0058218 0.07204929 6140.98 -13.960  <.0001

&nbsp;Personality - Values      Past    0.2611126 0.07204929 6140.98   3.624  0.0018

&nbsp;Personality - Life        Past   -0.7871010 0.07204929 6140.98 -10.924  <.0001

&nbsp;Values - Life             Past   -1.0482136 0.07204929 6140.98 -14.549  <.0001

&nbsp;Preferences - Values      Future  0.2217494 0.07204929 6140.98   3.078  0.0126

&nbsp;Preferences - Life        Future -0.9075714 0.07204929 6140.98 -12.597  <.0001

&nbsp;Personality - Values      Future  0.3085987 0.07204929 6140.98   4.283  0.0001

&nbsp;Personality - Life        Future -0.8207221 0.07204929 6140.98 -11.391  <.0001

&nbsp;Values - Life             Future -1.1293208 0.07204929 6140.98 -15.674  <.0001



Results are averaged over the levels of: TEMPORAL\_DO 

P value adjustment: bonferroni method for 6 tests 



Cohen's d calculated from raw data:

Comparison: Preferences - Personality | Past

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: -0.07681

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.01446



Comparison: Preferences - Life | Past

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: -0.35418

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Personality - Values | Past

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: 0.09073

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00175



Comparison: Personality - Life | Past

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: -0.27756

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Values - Life | Past

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: -0.36538

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Preferences - Values | Future

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: 0.07838

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.01257



Comparison: Preferences - Life | Future

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: -0.32051

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Personality - Values | Future

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: 0.10956

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00011



Comparison: Personality - Life | Future

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: -0.29009

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Values - Life | Future

&nbsp; n1 = 1063, n2 = 1063

&nbsp; Cohen's d: -0.39881

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



\[1] "\\n=== COHEN'S D FOR **TEMPORAL\_DO ├ù DOMAIN** INTERACTION ==="

Significant pairwise comparisons (p < 0.05):

&nbsp;contrast       DOMAIN  estimate        SE     df t.ratio p.value

&nbsp;01PAST - 02FUT Life   0.4227906 0.1572823 1579.2   2.688  0.0073



Results are averaged over the levels of: TIME 



Cohen's d calculated from raw data:

Comparison: 01PAST - 02FUT | Life

&nbsp; n1 = 1072, n2 = 1054

&nbsp; Cohen's d: 0.14893

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00726



Significant pairwise comparisons (p < 0.05):

&nbsp;contrast                  TEMPORAL\_DO   estimate         SE   df t.ratio

&nbsp;Preferences - Personality 01PAST      -0.2182836 0.07830983 3183  -2.787

&nbsp;Preferences - Life        01PAST      -1.1268657 0.07830983 3183 -14.390

&nbsp;Personality - Values      01PAST       0.3069030 0.07830983 3183   3.919

&nbsp;Personality - Life        01PAST      -0.9085821 0.07830983 3183 -11.602

&nbsp;Values - Life             01PAST      -1.2154851 0.07830983 3183 -15.521

&nbsp;Preferences - Life        02FUT       -0.7865275 0.07897567 3183  -9.959

&nbsp;Personality - Values      02FUT        0.2628083 0.07897567 3183   3.328

&nbsp;Personality - Life        02FUT       -0.6992410 0.07897567 3183  -8.854

&nbsp;Values - Life             02FUT       -0.9620493 0.07897567 3183 -12.182

&nbsp;p.value

&nbsp; 0.0321

&nbsp; <.0001

&nbsp; 0.0005

&nbsp; <.0001

&nbsp; <.0001

&nbsp; <.0001

&nbsp; 0.0053

&nbsp; <.0001

&nbsp; <.0001



Results are averaged over the levels of: TIME 

P value adjustment: bonferroni method for 6 tests 



Cohen's d calculated from raw data:

Comparison: Preferences - Personality | 01PAST

&nbsp; n1 = 1072, n2 = 1072

&nbsp; Cohen's d: -0.07591

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.03207



Comparison: Preferences - Life | 01PAST

&nbsp; n1 = 1072, n2 = 1072

&nbsp; Cohen's d: -0.39333

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Personality - Values | 01PAST

&nbsp; n1 = 1072, n2 = 1072

&nbsp; Cohen's d: 0.10722

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00054



Comparison: Personality - Life | 01PAST

&nbsp; n1 = 1072, n2 = 1072

&nbsp; Cohen's d: -0.31964

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Values - Life | 01PAST

&nbsp; n1 = 1072, n2 = 1072

&nbsp; Cohen's d: -0.42622

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Preferences - Life | 02FUT

&nbsp; n1 = 1054, n2 = 1054

&nbsp; Cohen's d: -0.27911

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Personality - Values | 02FUT

&nbsp; n1 = 1054, n2 = 1054

&nbsp; Cohen's d: 0.09213

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00531



Comparison: Personality - Life | 02FUT

&nbsp; n1 = 1054, n2 = 1054

&nbsp; Cohen's d: -0.24666

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



Comparison: Values - Life | 02FUT

&nbsp; n1 = 1054, n2 = 1054

&nbsp; Cohen's d: -0.33596

&nbsp; Effect size interpretation: small

&nbsp; p-value: 0.00000



\[1] "\\n=== **COHEN'S D FOR THREE-WAY INTERACTION** ==="

\[1] "The pairwise comparisons show the TIME effects within each TEMPORAL\_DO ├ù DOMAIN combination:"

**TEMPORAL\_DO = 01PAST, DOMAIN = Preferences:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.3638060 0.1061305 3523.81   3.428  0.0006**



**TEMPORAL\_DO = 02FUT, DOMAIN = Preferences:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.2580645 0.1070329 3523.81   2.411  0.0160**



**TEMPORAL\_DO = 01PAST, DOMAIN = Personality:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.4757463 0.1061305 3523.81   4.483  <.0001**



**TEMPORAL\_DO = 02FUT, DOMAIN = Personality:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.4098672 0.1070329 3523.81   3.829  0.0001**



**TEMPORAL\_DO = 01PAST, DOMAIN = Values:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.4701493 0.1061305 3523.81   4.430  <.0001**



**TEMPORAL\_DO = 02FUT, DOMAIN = Values:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.5104364 0.1070329 3523.81   4.769  <.0001**



**TEMPORAL\_DO = 01PAST, DOMAIN = Life:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.5242537 0.1061305 3523.81   4.940  <.0001**



**TEMPORAL\_DO = 02FUT, DOMAIN = Life:**

 **contrast       estimate        SE      df t.ratio p.value**

 **Past - Future 0.2941176 0.1070329 3523.81   2.748  0.0060**



\[1] "\\nCohen's d calculations for significant TIME effects within each TEMPORAL\_DO ├ù DOMAIN combination:"

**TEMPORAL\_DO = 01PAST, DOMAIN = Preferences:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 536, n\_Future = 536

  **Cohen's d: 0.12574**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00062

&nbsp; Estimated difference: 0.36381



**TEMPORAL\_DO = 02FUT, DOMAIN = Preferences:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 527, n\_Future = 527

  **Cohen's d: 0.09256**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.01596

&nbsp; Estimated difference: 0.25806



**TEMPORAL\_DO = 01PAST, DOMAIN = Personality:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 536, n\_Future = 536

  **Cohen's d: 0.16725**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00001

&nbsp; Estimated difference: 0.47575



**TEMPORAL\_DO = 02FUT, DOMAIN = Personality:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 527, n\_Future = 527

  **Cohen's d: 0.14547**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00013

&nbsp; Estimated difference: 0.40987



**TEMPORAL\_DO = 01PAST, DOMAIN = Values:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 536, n\_Future = 536

  **Cohen's d: 0.16420**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00001

&nbsp; Estimated difference: 0.47015



**TEMPORAL\_DO = 02FUT, DOMAIN = Values:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 527, n\_Future = 527

  **Cohen's d: 0.17779**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00000

&nbsp; Estimated difference: 0.51044



**TEMPORAL\_DO = 01PAST, DOMAIN = Life:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 536, n\_Future = 536

  **Cohen's d: 0.18584**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00000

&nbsp; Estimated difference: 0.52425



**TEMPORAL\_DO = 02FUT, DOMAIN = Life:**

&nbsp; Past vs Future comparison

&nbsp; n\_Past = 527, n\_Future = 527

  **Cohen's d: 0.10343**

&nbsp; Effect size interpretation: negligible

&nbsp; p-value: 0.00603

&nbsp; Estimated difference: 0.29412



\[1] "\\n=== ANALYSIS COMPLETE ==="

\[1] "All significant and marginal effects have been analyzed with Cohen's d calculations."



