--- title: "Meta-regressions of study-level continuous moderators" output: html_document: toc: true toc_depth: 4 number_sections: true toc_float: collapsed: false date: "`r format(Sys.time(), '%d %B %Y')`" author: - "**Code:** Andrew W Brown, PhD^[Indiana University - Bloomington]" - "Sara Lappan, PhD^[University of Alabama at Birmingham]" - "Peter Hendricks, PhD^[University of Alabama at Birmingham]" --- ### `r outname` ```{r echo=long, eval=TRUE, include=TRUE} cont.table.out <- cont.table(cont.out, outname) print(cont.out$model) cat(paste("\nICC:", fmt4(cont.out$ICC))) cat(paste("\nI^2.1", fmt1(cont.out$I2[1]))) cat(paste("\nI^2.2", fmt1(cont.out$I2[2]))) header <- 7 names(header) <- outname kable(cont.out$prediction) %>% add_header_above(header = header, align = 'l')%>% kable_styling(full_width = F) if(plots) plo.reg(cont.out, v, outname) ``` ```{r eval=TRUE, echo=FALSE, results='asis'} if(plots) cat("\n**Figure:** Meta-regression for '",outname,"'. The solid line represents the predicted dropout rate at the given predictor value; dashed lines represent the 95% CI; dotted lines represent the 95% Prediction Interval (PI). Points are proportional to the inverse variance of the individual dropout rates.") ```