Forestplot for SLMA models

Draws a foresplot of the coefficients for Study-Level Meta-Analysis performed with DataSHIELD

ds.forestplot(mod, variable = NULL, method = "ML", layout = "JAMA")

Arguments

mod

list List outputed by any of the SLMA models of DataSHIELD (ds.glmerSLMA, ds.glmSLMA, ds.lmerSLMA)

variable

character (default NULL) Variable to meta-analyze and visualize, by setting this argument to NULL (default) the first independent variable will be used.

method

character (Default "ML") Method to estimate the between study variance. See details from ?meta::metagen for the different options.

layout

character (default "JAMA") Layout of the plot. See details from ?meta::metagen for the different options.

Examples

if (FALSE) { # \dontrun{
  # Run a logistic regression
  
  builder <- DSI::newDSLoginBuilder()
  builder$append(server = "study1", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "CNSIM.CNSIM1", driver = "OpalDriver")
  builder$append(server = "study2", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "CNSIM.CNSIM2", driver = "OpalDriver")
  builder$append(server = "study3",
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "CNSIM.CNSIM3", driver = "OpalDriver")
  logindata <- builder$build()
  
  # Log onto the remote Opal training servers
  connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D") 
  
  # Fit the logistic regression model

  mod <- ds.glmSLMA(formula = "DIS_DIAB~GENDER+PM_BMI_CONTINUOUS+LAB_HDL",
                data = "D",
                family = "binomial",
                datasources = connections)
                
  # Plot the results of the model
  ds.forestplot(mod)
} # }