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Running MAs.R
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Running MAs.R
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library(meta)
#main models
models_beta <- map(datasets_beta,
~metagen(std_estimate,
std_error,
data = .,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
id = id))
models_or <- map(datasets_or,
~metagen(std_estimate,
std_error,
data = .,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
id = id))
models_smd <- map(datasets_smd,
~metagen(smd,
smd_std_error,
data = .,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
id = id))
#subgroup models
models_beta_subgroups <- map2(datasets_beta,
names(datasets_beta),
function(data, name) {
output <- list()
output$sex <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = gender,
id = id)
output$rct <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = study_design,
id = id)
output$age <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = age,
id = id)
output$poor <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = SG3_SEP,
id = id)
output$setting <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = SG4_setting,
id = id)
output$earned <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = SG1_earned,
id = id)
return(output)
})
models_beta_subgroups$ma1a$rob <- metagen(std_estimate,
std_error,
data = datasets_all_beta$ma1a,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = robcat2,
id = id)
models_beta_subgroups$ma1b$rob <- metagen(std_estimate,
std_error,
data = datasets_all_beta$ma1b,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = robcat2,
id = id)
models_or_subgroups <- map2(datasets_or,
names(datasets_or),
function(data, name) {
output <- list()
output$sex <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
byvar = gender,
id = id)
output$rct <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
byvar = study_design,
id = id)
output$age <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
byvar = age,
id = id)
output$poor <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
byvar = SG3_SEP,
id = id)
output$setting <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
byvar = SG4_setting,
id = id)
output$earned <- metagen(std_estimate,
std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
byvar = SG1_earned,
id = id)
return(output)
})
models_or_subgroups$ma1a2$rob <- metagen(std_estimate,
std_error,
data = datasets_all_or$ma1a2,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "OR",
n.e = n_people,
byvar = robcat2,
id = id)
models_smd_subgroups <- map2(datasets_smd,
names(datasets_smd),
function(data, name) {
output <- list()
output$sex <- metagen(smd,
smd_std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = gender,
id = id)
output$rct <- metagen(smd,
smd_std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = study_design,
id = id)
output$age <- metagen(smd,
smd_std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = age,
id = id)
output$poor <- metagen(smd,
smd_std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = SG3_SEP,
id = id)
output$setting <- metagen(smd,
smd_std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = SG4_setting,
id = id)
output$pov <- metagen(smd,
smd_std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
sm = "SMD",
n.e = n_people,
byvar= poverty,
id = id)
output$earned <- metagen(smd,
smd_std_error,
data = data,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
sm = "SMD",
n.e = n_people,
byvar= SG1_earned,
id = id)
return(output)
})
models_smd_subgroups$ma2a$rob <- metagen(smd,
smd_std_error,
data = datasets_all_smd$ma2a,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = robcat2,
id = id)
models_smd_subgroups$ma2b$rob <- metagen(smd,
smd_std_error,
data = datasets_all_smd$ma2b,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = robcat2,
id = id)
models_smd_subgroups$ma3a$rob <- metagen(smd,
smd_std_error,
data = datasets_all_smd$ma3a,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = robcat2,
id = id)
models_smd_subgroups$ma3b$rob <- metagen(smd,
smd_std_error,
data = datasets_all_smd$ma3b,
studlab = paste(first_author),
comb.fixed = FALSE,
comb.random = TRUE,
method.tau = "REML",
hakn = FALSE,
prediction = FALSE,
sm = "SMD",
n.e = n_people,
byvar = robcat2,
id = id)
# Models for likely poverty transition studies only
# models_pov <- map(datasets_pov,
# ~metagen(smd,
# smd_std_error,
# data = .,
# studlab = paste(first_author),
# comb.fixed = FALSE,
# comb.random = TRUE,
# method.tau = "REML",
# hakn = FALSE,
# prediction = FALSE,
# sm = "SMD",
# n.e = n_people,
# id = id))
#
# models_pov$ma2a_rob <- metagen(smd,
# smd_std_error,
# data = datasets_pov$ma2a,
# studlab = paste(first_author),
# comb.fixed = FALSE,
# comb.random = TRUE,
# method.tau = "REML",
# hakn = FALSE,
# prediction = FALSE,
# sm = "SMD",
# n.e = n_people,
# byvar = robcat2,
#id = id)
#
# models_pov$ma2b_rob <- metagen(smd,
# smd_std_error,
# data = datasets_pov$ma2b,
# studlab = paste(first_author),
# comb.fixed = FALSE,
# comb.random = TRUE,
# method.tau = "REML",
# hakn = FALSE,
# prediction = FALSE,
# sm = "SMD",
# n.e = n_people,
# byvar = robcat2,
#id = id)
# Dropping those we can't use before making forest plots
models_beta <- models_beta[
names(
models_beta
) %in% c("ma1a_poor") == FALSE]
models_beta_subgroups$ma1a <- models_beta_subgroups$ma1a[
names(
models_beta_subgroups$ma1a
) %in% c("rct", "poor") == FALSE]
models_beta_subgroups$ma1a_poor <- models_beta_subgroups$ma1a_poor[
names(
models_beta_subgroups$ma1a_poor
) %in% c("rct", "setting", "sex", "age", "rob", "earned") == FALSE]
models_beta_subgroups$ma1b <- models_beta_subgroups$ma1b[
names(
models_beta_subgroups$ma1b
) %in% c("rct") == FALSE]
models_smd_subgroups$ma3a <- models_smd_subgroups$ma3a[
names(
models_smd_subgroups$ma3a
) %in% c("rct", "poor", "pov") == FALSE]
models_or_subgroups$ma1a2 <- models_or_subgroups$ma1a2[
names(
models_or_subgroups$ma1a2
) %in% c("rct", "setting") == FALSE]
models_smd <- models_smd[
names(
models_smd
) %in% c("ma2b_sex") == FALSE]
models_smd_subgroups$ma2b <- models_smd_subgroups$ma2b[
names(
models_smd_subgroups$ma2b
) %in% c("sex") == FALSE]
models_smd_subgroups$ma2b_sex <- models_smd_subgroups$ma2b_sex[
names(
models_smd_subgroups$ma2b_sex
) %in% c("rct", "setting", "poor", "age", "rob", "pov", "earned", "pov") == FALSE]