Summarize the control quality of studies

Source: R/summarize_control_quality.R

summarize_control_quality() allows you to summarize how well studies control for variables within one or more domains, and how well those domains are controlled for overall. Each logical statement is a domain and can be named.

summarize_control_quality(.df, ..., domains = TRUE)

Arguments

.df

A data frame, usually the result of metaconfoundr()

...

Boolean arguments to declare adequate control logic

domains

Logical. Include the domains in the output? If FALSE, only returns overall control quality.

Value

A tibble

Examples


summary_df <- summarize_control_quality(
  metaconfoundr(ipi),
  Sociodemographics = `Maternal age` & `Race/ethnicity` & `Marital status`,
  Socioeconomics = `SES category` | Insurance & Education,
  "Reproductive Hx" = `Prior pregnancy outcome`
)

summary_df
#> # A tibble: 44 × 4
#>    study     variable          control_quality construct
#>    <chr>     <fct>             <ord>           <fct>    
#>  1 Zhu_2001a overall           some concerns   overall  
#>  2 Zhu_2001a Sociodemographics adequate        domains  
#>  3 Zhu_2001a Socioeconomics    inadequate      domains  
#>  4 Zhu_2001a Reproductive Hx   adequate        domains  
#>  5 Zhu_2001b overall           some concerns   overall  
#>  6 Zhu_2001b Sociodemographics adequate        domains  
#>  7 Zhu_2001b Socioeconomics    inadequate      domains  
#>  8 Zhu_2001b Reproductive Hx   adequate        domains  
#>  9 Zhu_1999  overall           some concerns   overall  
#> 10 Zhu_1999  Sociodemographics adequate        domains  
#> # … with 34 more rows

summary_df %>%
  mc_trafficlight() +
  theme_mc() +
  facet_constructs() +
  geom_cochrane() +
  scale_fill_cochrane()