estmeta: Meta-analysis of Beta (the parameters or coefficients...

In Package-Metaan-Rep/Metaan: Meta-Analysis of Published Epidemiological Studies

Description

Fixed effect model or DerSimonian and Laird-based Random effect model for standard meta-analysis of Beta (the parameters or coefficients) estimated from regression models (e.g linear regression or generalised linear regression models).

Usage

estmeta(Beta, u, l, test = c("FIXED", "RANDOM"), conf.level = 0.95)

Arguments

Beta	A numeric vector of Beta (the parameters or coefficients) estimated from the individual studies
u	A numeric vector of the upper bound of the confidence interval of the Beta reported from the individual studies.
l	A numeric vector of the lower bound of the confidence interval of the Beta reported from the individual studies.
test	Logical, indicating the statistical method to be used. "FIXED" for the fixed effect odel and "RANDOM" for the random effect model.
conf.level	Coverage for confidence interval

Value

Object of class "metaan.ra". A list that print the output from the priskran function. The following could be found from the list :

• rr_tot (Effect): The pooled effect from the individual studies' estimate (RR, OR, or HR)

• sd_tot_lnRR (SE-Log(Effect)): The standard error of the pooled effect (see reference Richardson et al 2020 for more details)

• l_tot (Lower CI): The lower confidence interval bound of the pooled effect (rr_tot)

• u_tot (Upper CI): The upper confidence interval bound of the pooled effect (rr_tot)

• Cochrane_stat (Cochran’s Q statistic): The value of the Cochrane's statistic of inter-study heterogeneity

• Degree_freedom (Degree of Freedom): The degree of freedom

• p_value (P-Value): The p-value of the statistic of Cochrane

• I_square (Higgins’ and Thompson’s I^2 (%)): I square value in percent (%) indicating the amount of the inter-study heterogeneity

Examples

study <- c("Canada", "Northern USA", "Chicago", "Georgia","Puerto", "Comm",
"Madanapalle", "UK", "South Africa", "Haiti", "Madras")
beta<- c(0.205, 0.411, 0.254, 1.562, 0.712, 0.983, 0.804, 0.237, 0.625,
0.198, 1.012)
lower_ci <- c(0.086, 0.134, 0.149, 0.374, 0.573, 0.582, 0.516, 0.179, 0.393,
0.078, 0.895)
upper_ci <- c(0.486, 1.257, 0.431, 6.528, 0.886, 1.659, 1.254,
0.312, 0.996, 0.499, 1.145)

donne <- data.frame(cbind(study, beta, lower_ci, upper_ci))

donne$beta <- as.numeric(as.character(donne$beta))
donne$upper_ci <- as.numeric(as.character(donne$upper_ci))
donne$lower_ci <- as.numeric(as.character(donne$lower_ci))


estmeta(Beta=donne$Risk, u=donne$upper_ci, l=donne$lower_ci, test="RANDOM")
estmeta(Beta=donne$Risk, u=donne$upper_ci, l=donne$lower_ci, test="FIXED")

Package-Metaan-Rep/Metaan documentation built on Dec. 28, 2021, 6:40 a.m.