ME_DATA_PATH <- here("data/0_metaanalysis_data.csv")
ma_raw <- read_csv(ME_DATA_PATH) %>%
select(1:4, 6:8, 10:16, 18,19,21, 27:29, 31:34, 48:50, 59) %>%
mutate_if(is.character, as.factor)
AVG_MONTH <- 30.43688
ma_c <- ma_raw %>%
filter(!is.na(d_calc)) %>%
mutate(mean_age = mean_age_1/AVG_MONTH,
year = as.numeric(str_sub(short_cite, -5, -2)),
condition_type = as.factor(ifelse(infant_type == "typical" & ME_trial_type == "FN", "TFN",
ifelse(infant_type == "typical" & ME_trial_type == "NN", "TNN",
as.character(infant_type))))) %>%
filter(mean_age < 144) multilingual data
test_data <- filter(ma_c, infant_type == "multilingual") %>%
select(2,8,9,10,11,12,13, 26, 27, 29)
DT::datatable(test_data)No grouping by infant
model1 <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
random = ~ 1 | short_cite,
method = "REML",
data = test_data)
summary(model1)##
## Multivariate Meta-Analysis Model (k = 12; method: REML)
##
## logLik Deviance AIC BIC AICc
## -5.3870 10.7740 16.7740 17.6818 20.7740
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4922 0.7016 6 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 10) = 65.1730, p-val < .0001
##
## Test of Moderators (coefficient(s) 2):
## QM(df = 1) = 3.1439, p-val = 0.0762
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0452 0.4200 0.1077 0.9142 -0.7779 0.8684
## mean_age 0.0155 0.0088 1.7731 0.0762 -0.0016 0.0327 .
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Grouping by infant
model2 <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
random = ~ 1 | same_infant/short_cite,
method = "REML",
data = test_data)
summary(model2)##
## Multivariate Meta-Analysis Model (k = 12; method: REML)
##
## logLik Deviance AIC BIC AICc
## -10.5686 21.1372 29.1372 30.3475 37.1372
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 0.2024 0.4499 12 no same_infant
## sigma^2.2 0.2024 0.4499 12 no same_infant/short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 10) = 65.1730, p-val < .0001
##
## Test of Moderators (coefficient(s) 2):
## QM(df = 1) = 3.9434, p-val = 0.0471
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1068 0.4387 -0.2435 0.8076 -0.9667 0.7531
## mean_age 0.0192 0.0097 1.9858 0.0471 0.0002 0.0381 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1