R/summaryTableFx.R

In enaY15/TabulationAutomation: Auomated analysis and tabulation of results

#' Summary Table Maker
#'
#' @param family e.g. Gaussian; argument for glm
#' @param analysis Analysis that produced data for regression analyses: "cfa", "bf", or "lca"
#' @param n.classes Number of classes if LCA
#' @param outcomeVar Outcome variable name
#' @param n.roundDigits Number of digits to round to
#' @param minDecimals Minimum number of decimal places to retain (to line up, in case trailing .00)
#' @param data Data to analyze
#'
#' @return table matrix
#' @export
summaryTableFx <- function(family = 'gaussian', analysis = 'cfa', n.classes = NULL, preds,
                           outcomeVar, n.roundDigits = 2, minDecimals = 2, data) {

  require(stats); require(data.table)
  #outcomeVar = outcomes[outcomeVar]
  ## Use standardized names for data to load data
  if (analysis == 'lca') {
    data <- lca
    preds <- paste0('Class', 1:n.classes) # predictors ('Class1' factor variable for 1-class lca, etc.)
  } else {
    preds <- paste0(preds, collapse = ' + ') # adding predictors (factors)
  }
  # if (analysis == 'cfa') {
  #   eval(parse(text = paste0('data <- data_cfa_', modelName))) # if cfa model names
  #   }
  if (analysis == 'bf') {
    #eval(parse(text = paste0('data <- data_bf_', modelName))) # if cfa model names
    preds <- paste0('GENERAL + ', preds) # add general factor to predictor list for bifactor models
  }
  # if (analysis == 'bcfa') {
  #   eval(parse(text = paste0('data <- data_bcfa_', modelName))) # if cfa model names
  # }

  formula <- paste0(outcomeVar, ' ~ ', preds) # create formula

  if (family == 'gaussian') {
    p <- 'Pr(>|t|)'  # p-value name if continuous outcome
  } else {
    p <- 'Pr(>|z|)' # p-value name if binary outcome
  }

  force(n.roundDigits); force(minDecimals)

  table <- eval(parse(text = paste0('format(round(coef(summary(
                                    glm(family = family, formula = formula, data = data)))
                                    [, c(\"Estimate\", \"Std. Error\", \"', p, '\")], ',
                                    n.roundDigits, '), nsmall = ', minDecimals, ')')))
  #dimnames(table)[[2]] <- c("Estimate", "SE", p)
  #dimnames(table)[[1]] <- gsub(dimnames(table)[[1]], pattern = '_', replacement = ' ')
  # tableRows <- dim(table)[1]
  # tableCols <- dim(table)[2]
  # table <- matrix(as.numeric(table), nrow = tableRows, ncol = tableCols)

  ## Warnings
  if (is.factor(data$outcomeVar) | is.character(data$outcomeVar)) {
    if (family == 'gaussian') {
      warning('Family argument is set to Gaussian by default.
              The specified outcome variable is a factor or string. Re-check these specifications.')
    }
  }

  print(table)
  return(table)

}