psacr002_sim.Rmd

---
title: "PSA CR 002: Cognitive Reappraisal"
date: "24/03/2020"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


```{r}
#devtools::install_github("scienceverse/scienceverse")
library(scienceverse)
library(tidyverse)
library(purrr)
library(afex)
library(broom)
```

## Set up Study

```{r}
study2 <- study("PSA CR 002: Using Reappraisal to Regulate Negative Emotion Concerning COVID-19")
```

## Confirmaory Hypothesis

```{r}

alpha <- 0.05 / 3

study2 <- add_hypothesis(study2, "confirmatory", "Using reappraisal would reduce negative emotion, catastrophic thoughts, and rumination concerning COVID-19.") %>%
  add_analysis("negemo", {
    a <- afex::aov_ez(id = "id", 
                      dv = "negemo",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("negemo", "Pr(>F)", "<", alpha) %>%
  add_analysis("catthoughts", {
    a <- afex::aov_ez(id = "id", 
                      dv = "catthoughts",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("catthoughts", "Pr(>F)", "<", alpha) %>%
  add_analysis("rumination", {
    a <- afex::aov_ez(id = "id", 
                      dv = "rumination",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("rumination", "Pr(>F)", "<", alpha) %>%
  add_eval("corroboration", "There is a significant main effect of condition on negative emotion, catastrophic thoughts, or rumination", "negemo | catthoughts | rumination")

```

## Manipulation Checks

```{r}

alpha <- 0.05

study2 <- add_hypothesis(study2, "manip_check", "emotion regulation frequency and success") %>%
  add_analysis("frequency", {
    a <- afex::aov_ez(id = "id", 
                      dv = "frequency",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("frequency", "Pr(>F)", "<", alpha) %>%
  add_analysis("success", {
    a <- afex::aov_ez(id = "id", 
                      dv = "success",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("success", "Pr(>F)", "<", alpha) %>%
  add_eval("corroboration", "There is a significant main effect of condition on frequency and success", "frequency & success")
```

## Exploratory Analyses

```{r}

alpha <- 0.05 / 3

study2 <- add_hypothesis(study2, "exploratory", "resilience, beliefs and behavioral intentions around COVID-19") %>%
  add_analysis("resilience", {
    a <- afex::aov_ez(id = "id", 
                      dv = "resilience",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("resilience", "Pr(>F)", "<", alpha) %>%
  add_analysis("beliefs", {
    a <- afex::aov_ez(id = "id", 
                      dv = "beliefs",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("beliefs", "Pr(>F)", "<", alpha) %>%
  add_analysis("intentions", {
    a <- afex::aov_ez(id = "id", 
                      dv = "intentions",
                      between = "condition", 
                      data = dat)
    a$anova_table
  }) %>%
  add_criterion("intentions", "Pr(>F)", "<", alpha) %>%
  add_eval("corroboration", "There is a significant main effect of condition on resilience, beliefs, or intentions", "resilience | beliefs | intentions")
```

## Simulate Data

```{r}
study2 <- add_sim_data(study2, "dat", 
    between = list(
      condition = c("reappraisal", "suppression", "noreg"),
      sex = c("male", "female")
    ), 
    within = list(
      measure = c("negemo", 
                  "catthoughts", 
                  "rumination",
                  "frequency", 
                  "success", 
                  "resilience", 
                  "beliefs", 
                  "intentions")
    ),
    n = 90,
    mu = list(reappraisal_male = 0.36, 
              reappraisal_female = 0.36,
              suppression_male = 0,
              suppression_female = 0,
              noreg_male = 0,
              noreg_female = 0
              ),
    dv = "score",
    long = FALSE
  )
```

```{r, out.width = "100%", fig.width=8, fig.height=5}
study2$data[[1]]$data %>%
  gather(measure, score, negemo:intentions) %>%
  ggplot(aes(condition, score)) + 
  geom_violin() + 
  stat_summary(fun.data = mean_se) +
  facet_wrap(~measure, nrow = 2)
```


```{r}
study2 <- study_analyse(study2)
```

```{r}
study_report(study2, "prereg", "PSACR_002_prereg.html")
study_report(study2, "postreg", "PSACR_002_post_sim.html")
```