Nback_mean Nback_SD Nback_med 53. 16667 31.24053 60 > df %>% + summarize( + dat_mean = mean(dat, na. rm = T), + dat_SD = sd(dat, na. rm = T), + dat_med = median(dat, na. rm = T)) dat_mean dat_SD dat_med 1 77 . 44245 5. 409394 77.39475 > #Correlation > cor . test(df$dat, df$Nback) The above where generated from R studio (revealing descriptive statistics). > emmeans(al_dat, ~Emotionstate) NOTE: Results may be misleading due to involvement in interactions Emotionstate emmean SE df lower. CL upper . CL negative 77 .8 1.60 20 74.5 81.2 positive 76.9 1.75 20 73.3 80.6 > emmeans (al_dat, ~Levelstress) NOTE: Results may be misleading due to involvement in interactions Levelstress emmean SE of lower. CL upper . CL agitation 77.5 1.60 20 74.1 80.8 no_agitation 77.3 1.75 20 73.7 80.9 > emmeans(a2_Nback, ~Emotionstate) NOTE: Results may be misleading due to involvement in interactions Emotionstate emmean SE df lower. CL upper. CL negative 60.3 8. 46 20 42.7 78.0 positive 43.1 9.21 20 23.9 62.3 > emmeans(a2_Nback, ~Levelstress) NOTE: Results may be misleading due to involvement in interactions Levelstress emmean SE of lower. CL upper. CL agitation 60.8 8. 46 20 43.2 78.5 no_agitation 42.6 9.21 20 23.4 61.8 Here are the marginal effects^ Now, make a table for working memory and the DAT test. similar to the below example. example of putting data into table for DAT: (not correct I believe :() DVs: Divergent IV1: emotions Marginal Means thinking IV2: stress Level 1: Level 2: N/A emotion positive emotion negative Level 1: 78.2 76.4 77.3 stress absent Level 2: 77.5 77.5 77.5 stress present Marginal Means 77.8 76.9 N/A