教學習作：如何運用模擬研究解析小樣本研究的證據力

get_params(weight_dat) %>% knitr::kable()

head(weight_sim) %>% knitr::kable()

weight_dat_list <- map(r_cand, function(x) sim_design( n = 7, ## 受試者人數 within = list(cond = c(“baseline”, “final”)), ## 獨變項設定 mu = data.frame(baseline=112.98, final=103.73), ## 基準及結束平均值 sd = data.frame(baseline=19.93, final=17.89), ## 基準及結束標準差 r = x, ## 基準及結束相關係數 dv=“weight”, long = TRUE, rep=1000 )) %>% set_names(nm=r_cand)

names(weight_sim_power) <- r_cand knitr::kable(t(weight_sim_power))

mass_dat_list <- map(r_cand, function(x) sim_design( n = 7, ## 受試者人數 within = list(cond = c(“baseline”, “final”)), ## 獨變項設定 mu = data.frame(baseline=39.38, final=35.98), ## 基準及結束平均值 sd = data.frame(baseline=4.10, final=4.46), ## 基準及結束標準差 r = x, ## 基準及結束相關係數 dv=“mass”, long = TRUE, rep=1000 )) %>% set_names(nm=r_cand)

analyse <- function(data) { t.test(mass ~ cond, data, paired = TRUE) %>% broom::tidy() }

names(mass_sim_power) <- r_cand knitr::kable(t(mass_sim_power))

BMI_dat_list <- map(r_cand, function(x) sim_design( n = 7, ## 受試者人數 within = list(cond = c(“baseline”, “final”)), ## 獨變項設定 mu = data.frame(baseline=34.62, final=31.73), ## 基準及結束平均值 sd = data.frame(baseline=3.27, final=2.89), ## 基準及結束標準差 r = x, ## 基準及結束相關係數 dv=“BMI”, long = TRUE, rep=1000 )) %>% set_names(nm=r_cand)

analyse <- function(data) { t.test(BMI ~ cond, data, paired = TRUE) %>% broom::tidy() }

names(BMI_sim_power) <- r_cand knitr::kable(t(BMI_sim_power))