RTmodels.Rmd
anjie & gal
Load data
RT_data <- read_csv(here('data/processed_data/processed_RTdata.csv'))## Parsed with column specification:
## cols(
## subject = col_character(),
## block_number = col_double(),
## block_type = col_character(),
## trial_number = col_double(),
## item_type = col_character(),
## trial_type = col_character(),
## trial_complexity = col_character(),
## item_id = col_character(),
## rt = col_double()
## )Model
- model <- log(rt) ~ trial_number * item_type * trial_complexity + (1|subject) + (1|item)
- model <- log(rt) ~ trial_number * item_type * trial_complexity + (1|subject)
- model <- log(rt) ~ trial_number * item_type * trial_complexity + (trial_number * item_type * trial_complexity|subject)
- model <- log(rt) ~ trial_number * item_type * trial_complexity + (trial_number * item_type * trial_complexity|subject) + (trial_number * item_type * trial_complexity|item)
starts with the third one and prune; we don’t need item level: https://osf.io/zqzsu/wiki/Standard%20Analytic%20Procedures/
model <- lmer('log(rt) ~ trial_number*item_type*trial_complexity + (trial_complexity*item_type*trial_number|subject)', data=RT_data, REML=FALSE)## boundary (singular) fit: see ?isSingular## Warning: Model failed to converge with 3 negative eigenvalues: -1.4e-01 -8.3e-01
## -2.1e+01broom.mixed::tidy(model) %>%
knitr::kable()## Registered S3 method overwritten by 'broom.mixed':
## method from
## tidy.gamlss broom| effect | group | term | estimate | std.error | statistic | df | p.value |
|---|---|---|---|---|---|---|---|
| fixed | NA | (Intercept) | 6.9344997 | 0.2190432 | 31.6581304 | 10.93329 | 0.0000000 |
| fixed | NA | trial_number | -0.0574003 | 0.0201967 | -2.8420679 | 15.30510 | 0.0121736 |
| fixed | NA | item_typedissimilar deviant | -0.0768674 | 0.3963564 | -0.1939350 | 15.73691 | 0.8487080 |
| fixed | NA | item_typesimilar deviant | -0.0913951 | 0.5387375 | -0.1696468 | 24.55833 | 0.8666777 |
| fixed | NA | trial_complexitysimple | -0.2111237 | 0.1118483 | -1.8875899 | 27.87998 | 0.0695312 |
| fixed | NA | trial_number:item_typedissimilar deviant | 0.0657620 | 0.0719134 | 0.9144608 | 19.29317 | 0.3717627 |
| fixed | NA | trial_number:item_typesimilar deviant | 0.0941119 | 0.0938169 | 1.0031451 | 23.50166 | 0.3260082 |
| fixed | NA | trial_number:trial_complexitysimple | 0.0207975 | 0.0212142 | 0.9803551 | 110.13962 | 0.3290594 |
| fixed | NA | item_typedissimilar deviant:trial_complexitysimple | 0.6167637 | 0.6288624 | 0.9807610 | 10.85209 | 0.3480698 |
| fixed | NA | item_typesimilar deviant:trial_complexitysimple | 0.4027131 | 0.7812956 | 0.5154427 | 25.01745 | 0.6107689 |
| fixed | NA | trial_number:item_typedissimilar deviant:trial_complexitysimple | -0.0846720 | 0.1069128 | -0.7919721 | 14.11802 | 0.4414815 |
| fixed | NA | trial_number:item_typesimilar deviant:trial_complexitysimple | -0.0957245 | 0.1323475 | -0.7232813 | 24.71198 | 0.4762980 |
| ran_pars | subject | sd__(Intercept) | 0.7164566 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).trial_complexitysimple | -0.2787160 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).item_typedissimilar deviant | 0.0189808 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).item_typesimilar deviant | 0.3804469 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).trial_number | -0.4892527 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).trial_complexitysimple:item_typedissimilar deviant | -0.1928030 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).trial_complexitysimple:item_typesimilar deviant | -0.2486167 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).trial_complexitysimple:trial_number | 0.8531746 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).item_typedissimilar deviant:trial_number | 0.0954455 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).item_typesimilar deviant:trial_number | -0.2237743 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).trial_complexitysimple:item_typedissimilar deviant:trial_number | 0.0235207 | NA | NA | NA | NA |
| ran_pars | subject | cor__(Intercept).trial_complexitysimple:item_typesimilar deviant:trial_number | 0.1755292 | NA | NA | NA | NA |
| ran_pars | subject | sd__trial_complexitysimple | 0.1586281 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.item_typedissimilar deviant | -0.2417078 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.item_typesimilar deviant | -0.0619827 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.trial_number | 0.6464785 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.trial_complexitysimple:item_typedissimilar deviant | 0.0456559 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.trial_complexitysimple:item_typesimilar deviant | 0.1889216 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.trial_complexitysimple:trial_number | -0.4936370 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.item_typedissimilar deviant:trial_number | 0.2722096 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.item_typesimilar deviant:trial_number | -0.0311456 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.trial_complexitysimple:item_typedissimilar deviant:trial_number | -0.1706822 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple.trial_complexitysimple:item_typesimilar deviant:trial_number | -0.0638767 | NA | NA | NA | NA |
| ran_pars | subject | sd__item_typedissimilar deviant | 0.4918765 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.item_typesimilar deviant | -0.1768349 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.trial_number | 0.1004619 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.trial_complexitysimple:item_typedissimilar deviant | -0.8833042 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.trial_complexitysimple:item_typesimilar deviant | 0.0831708 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.trial_complexitysimple:trial_number | -0.2175285 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.item_typedissimilar deviant:trial_number | -0.8894402 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.item_typesimilar deviant:trial_number | 0.1119111 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.trial_complexitysimple:item_typedissimilar deviant:trial_number | 0.8616081 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant.trial_complexitysimple:item_typesimilar deviant:trial_number | -0.1754693 | NA | NA | NA | NA |
| ran_pars | subject | sd__item_typesimilar deviant | 1.0891933 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.trial_number | 0.3791560 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.trial_complexitysimple:item_typedissimilar deviant | 0.2498691 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.trial_complexitysimple:item_typesimilar deviant | -0.9215194 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.trial_complexitysimple:trial_number | 0.6106855 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.item_typedissimilar deviant:trial_number | -0.1470875 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.item_typesimilar deviant:trial_number | -0.9793436 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.trial_complexitysimple:item_typedissimilar deviant:trial_number | -0.3664484 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant.trial_complexitysimple:item_typesimilar deviant:trial_number | 0.9410307 | NA | NA | NA | NA |
| ran_pars | subject | sd__trial_number | 0.0483461 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_number.trial_complexitysimple:item_typedissimilar deviant | -0.0209861 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_number.trial_complexitysimple:item_typesimilar deviant | -0.3595039 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_number.trial_complexitysimple:trial_number | -0.4622758 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_number.item_typedissimilar deviant:trial_number | -0.3376881 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_number.item_typesimilar deviant:trial_number | -0.5404287 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_number.trial_complexitysimple:item_typedissimilar deviant:trial_number | -0.0469972 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_number.trial_complexitysimple:item_typesimilar deviant:trial_number | 0.4584926 | NA | NA | NA | NA |
| ran_pars | subject | sd__trial_complexitysimple:item_typedissimilar deviant | 1.0543380 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typedissimilar deviant.trial_complexitysimple:item_typesimilar deviant | -0.2104109 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typedissimilar deviant.trial_complexitysimple:trial_number | 0.1618861 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typedissimilar deviant.item_typedissimilar deviant:trial_number | 0.6954830 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typedissimilar deviant.item_typesimilar deviant:trial_number | -0.2234659 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typedissimilar deviant.trial_complexitysimple:item_typedissimilar deviant:trial_number | -0.9472046 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typedissimilar deviant.trial_complexitysimple:item_typesimilar deviant:trial_number | 0.3066464 | NA | NA | NA | NA |
| ran_pars | subject | sd__trial_complexitysimple:item_typesimilar deviant | 1.6591258 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typesimilar deviant.trial_complexitysimple:trial_number | -0.4644045 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typesimilar deviant.item_typedissimilar deviant:trial_number | 0.3193080 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typesimilar deviant.item_typesimilar deviant:trial_number | 0.8994036 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typesimilar deviant.trial_complexitysimple:item_typedissimilar deviant:trial_number | 0.2189353 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typesimilar deviant.trial_complexitysimple:item_typesimilar deviant:trial_number | -0.9851634 | NA | NA | NA | NA |
| ran_pars | subject | sd__trial_complexitysimple:trial_number | 0.0170135 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:trial_number.item_typedissimilar deviant:trial_number | 0.1890156 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:trial_number.item_typesimilar deviant:trial_number | -0.4615933 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:trial_number.trial_complexitysimple:item_typedissimilar deviant:trial_number | -0.2843284 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:trial_number.trial_complexitysimple:item_typesimilar deviant:trial_number | 0.4125547 | NA | NA | NA | NA |
| ran_pars | subject | sd__item_typedissimilar deviant:trial_number | 0.0970377 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant:trial_number.item_typesimilar deviant:trial_number | 0.2261569 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant:trial_number.trial_complexitysimple:item_typedissimilar deviant:trial_number | -0.7273896 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typedissimilar deviant:trial_number.trial_complexitysimple:item_typesimilar deviant:trial_number | -0.2349299 | NA | NA | NA | NA |
| ran_pars | subject | sd__item_typesimilar deviant:trial_number | 0.1924552 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant:trial_number.trial_complexitysimple:item_typedissimilar deviant:trial_number | 0.3430358 | NA | NA | NA | NA |
| ran_pars | subject | cor__item_typesimilar deviant:trial_number.trial_complexitysimple:item_typesimilar deviant:trial_number | -0.9374133 | NA | NA | NA | NA |
| ran_pars | subject | sd__trial_complexitysimple:item_typedissimilar deviant:trial_number | 0.1511353 | NA | NA | NA | NA |
| ran_pars | subject | cor__trial_complexitysimple:item_typedissimilar deviant:trial_number.trial_complexitysimple:item_typesimilar deviant:trial_number | -0.3351649 | NA | NA | NA | NA |
| ran_pars | subject | sd__trial_complexitysimple:item_typesimilar deviant:trial_number | 0.2653946 | NA | NA | NA | NA |
| ran_pars | Residual | sd__Observation | 0.9854210 | NA | NA | NA | NA |
xtable(summary(model)$coefficients)## % latex table generated in R 3.6.2 by xtable 1.8-4 package
## % Tue Feb 9 21:23:13 2021
## \begin{table}[ht]
## \centering
## \begin{tabular}{rrrrrr}
## \hline
## & Estimate & Std. Error & df & t value & Pr($>$$|$t$|$) \\
## \hline
## (Intercept) & 6.93 & 0.22 & 10.93 & 31.66 & 0.00 \\
## trial\_number & -0.06 & 0.02 & 15.31 & -2.84 & 0.01 \\
## item\_typedissimilar deviant & -0.08 & 0.40 & 15.74 & -0.19 & 0.85 \\
## item\_typesimilar deviant & -0.09 & 0.54 & 24.56 & -0.17 & 0.87 \\
## trial\_complexitysimple & -0.21 & 0.11 & 27.88 & -1.89 & 0.07 \\
## trial\_number:item\_typedissimilar deviant & 0.07 & 0.07 & 19.29 & 0.91 & 0.37 \\
## trial\_number:item\_typesimilar deviant & 0.09 & 0.09 & 23.50 & 1.00 & 0.33 \\
## trial\_number:trial\_complexitysimple & 0.02 & 0.02 & 110.14 & 0.98 & 0.33 \\
## item\_typedissimilar deviant:trial\_complexitysimple & 0.62 & 0.63 & 10.85 & 0.98 & 0.35 \\
## item\_typesimilar deviant:trial\_complexitysimple & 0.40 & 0.78 & 25.02 & 0.52 & 0.61 \\
## trial\_number:item\_typedissimilar deviant:trial\_complexitysimple & -0.08 & 0.11 & 14.12 & -0.79 & 0.44 \\
## trial\_number:item\_typesimilar deviant:trial\_complexitysimple & -0.10 & 0.13 & 24.71 & -0.72 & 0.48 \\
## \hline
## \end{tabular}
## \end{table}plot(model)
qqnorm(residuals(model))
qqline(residuals(model))