3_External_review

[arranhamlet]

Added a section on weighted regression using the survey package and gtsummary.

Weighted regression

Another tool we can use to analyse our survey data is to use weighted regression. This allows us to carry out to account for the survey design in our regression in order to avoid biases that may be introduced from the survey process.

To carry out a univariate regression, we can use the packages survey for the function svyglm() and the package gtsummary which allows us to call svyglm() inside the function tbl_uvregression. To do this we first use the survey_design object created above. This is then provided to the function tbl_uvregression() as in the Univariate and multivariable regression chapter. We then make one key change, we change method = glm to method = survey::svyglm in order to carry out our survey weighted regression.

Here we will be using the previously created object survey_design to predict whether the value in the column died is TRUE, using the columns malaria_treatment, bednet, and age_years.

survey_design %>%
     tbl_uvregression(                             #Carry out a univariate regression, if we wanted a multivariable regression we would use tbl_
          method = survey::svyglm,                 #Set this to survey::svyglm to carry out our weighted regression on the survey data
          y = died,                                #The column we are trying to predict
          method.args = list(family = binomial),   #The family, we are carrying out a logistic regression so we want the family as binomial
          include = c(malaria_treatment,           #These are the columns we want to evaluate
                      bednet,
                      age_years),
          exponentiate = T                         #To transform the log odds to odds ratio for easier interpretation
     )

If we wanted to carry out a multivariable regression, we would have to first use the function svyglm() and pipe (%>%) the results into the function tbl_regression. Note that we need to specify the formula.

survey_design %>%
     svyglm(formula = died ~ malaria_treatment + 
                 bednet + 
                 age_years,
            family = binomial) %>%                   #The family, we are carrying out a logistic regression so we want the family as binomial
     tbl_regression( 
          exponentiate = T                           #To transform the log odds to odds ratio for easier interpretation                            
     )