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. 2023 Nov 28;36:17. doi: 10.5334/irsp.883

Table 7.

All analyses re-run, split by whether Study 1 or Study 2 was presented first.


ANALYSIS STATISTICAL TEST AND FACTORS FULL SAMPLE N = 821 STUDY 1 FIRST N = 393 STUDY 2 FIRST N = 428



ES p ES p ES p

Replication analyses

Study 1: Forced choice Chi-square .38 < .001 .41 < .001 .36 < .001

Study 1: Preference Independent samples t-test –.79 < .001 –.74 < .001 –.84 < .001

Study 2: Time domain Chi-square .32 < .001 .36 < .001 .29 < .001

Study 2: Money domain Chi-square .23 < .001 .28 < .001 .19 < .001

Study 5: Preference between-groups ANOVA opportunity cost .00 .284 .01 .118 .00 .969

education .00 .150 .01 .058 .00 .850

opportunity cost × education .00 .308 .00 .359 .00 .527

Study 5: Forced choice Generalized Linear Model opportunity cost .97 .951 1.40 .619 .68 .570

education 1.21 .552 1.75 .207 .82 .693

opportunity cost × education 2.00 .285 1.22 .825 3.69 .185

Additional analyses and checks

Study 2 re-analysis Logistic Regression sunk domain 1.17 .414 1.01 .960 1.35 .282

sunk presence .20 < .001 .15 < .001 .26 < .001

sunk type × sunk presence .53 .142 .49 .291 .55 .297

Study 1 versus Study 5: Analysis of within subject effects Linear model opportunity cost .09 .758 .35 .370 –.23 .566

study .15 .437 .03 .901 .29 .308

education .22 .273 .44 .118 .05 .852

opportunity cost × study –.46 .240 –.38 .486 –.54 .342

opportunity cost × education .48 .228 .42 .457 .65 .234

study × education .08 .770 .33 .412 –.18 .647

opportunity cost × study × education .31 .578 –.01 .986 .62 .424

Generalized Linear Model opportunity cost .97 .951 1.40 .619 .68 .570

study 1.37 .311 1.23 .650 1.43 .436

education 1.21 .552 1.75 .207 .82 .693

opportunity cost × study .65 .497 .93 .939 .49 .436

opportunity cost × education 2.00 .285 1.22 .825 3.69 .185

study × education 1.04 .922 1.24 .722 .94 .928

opportunity cost × study × education 1.67 .551 1.29 .832 2.02 .597

Note. Reported effect sizes (ES) are: Chi-square – ϕc, Independent samples t-test – Cohen’s d, ANOVA –, Generalized Linear Model and Logistic Regression – Odds Ratios, Linear model – β.