R/CheckRowAndColumnSumValuesAreValid.r

In CausalR: Causal network analysis methods

#' @title check row and column sum values are valid
#' @description
#' Checkes to see if the values of r+, r-, c+ and c- which are stored in rowAndColumnSumValues define a valid contingency
#' table
#' @param rowAndColumnSumValues  a 4x1 vector containing the row and column sum values (r+, r-, c+, c-) for a 2x2 contingency table
#' @param predictionListStats a vector containing the values q+, q- and q0 
#' @param experimentalResultStats A vector containing the values n+, n- and n0
#' @return TRUE if the table is valid; otherwise FALSE


# Check if the values of r+, r-, c+ and c- which are stored in rowAndColumnSumValues make up a valid contingency table in relation to the whole 3x3
# table

# Inputs: rowAndColumnSumValues A 4x1 vector containing the row and column sum values (r+, r-, c+, c-) for a 2x2 contingency table
# predictionListStats A vector containing the values q+, q- and q0 (the number of positive/negative/non-significant (or contradictory) predictions)
# experimentalResultStats A vector containing the values n+, n- and n0 (the number of positive/negative/non-significant (or contradictory)
# transcripts in the results)



CheckRowAndColumnSumValuesAreValid <- function(rowAndColumnSumValues, predictionListStats, experimentalResultStats) {
    
    # r+ and r-
    r_p <- rowAndColumnSumValues[1]
    r_m <- rowAndColumnSumValues[2]
    # c+ and c-
    c_p <- rowAndColumnSumValues[3]
    c_m <- rowAndColumnSumValues[4]
    
    if (c_m < 0) {
        return(FALSE)
    }
    
    # q+, q- and q0
    q_p <- predictionListStats[1]
    q_m <- predictionListStats[2]
    q_z <- predictionListStats[3]
    
    # n+, n- and n0
    n_p <- experimentalResultStats[1]
    n_m <- experimentalResultStats[2]
    
    # Compute the other values in the 3x3 table
    
    n_pz <- q_p - r_p
    if (n_pz < 0) {
        return(FALSE)
    }
    
    n_mz <- q_m - r_m
    if (n_mz < 0) {
        return(FALSE)
    }
    
    n_zp <- n_p - c_p
    if (n_zp < 0) {
        return(FALSE)
    }
    
    n_zm <- n_m - c_m
    if (n_zm < 0) {
        return(FALSE)
    }
    
    n_zz <- q_z - (n_zp + n_zm)
    
    if (n_zz < 0) {
        return(FALSE)
    }
    
    return(TRUE)
}