CheckAllAssumptionsANCOVA: Checks assumptions for ANOVA/ANCOVA

In yhhc2/ancovall: Package that automates the process of doing ANCOVA on a large number of dependent variables

Description

Returns information that can be used to determine if assumptions for ANCOVA are met.

Usage

CheckAllAssumptionsANCOVA(
  inputted.data,
  dependent.variable,
  independent.variable,
  covariates
)

Arguments

inputted.data	A dataframe
dependent.variable	A string that specifies the column name of the column to use as the dependent variable. Column must be numeric.
independent.variable	A string that specifies the column name of the column to use as the independent variable. Column can be numeric or factor. If it's a factor, then it can only have two levels.
covariates	A vector of strings that specifies the columns names of the columns to be used as covariates. Columns can be numeric or factor. If it's a factor, then it can only have two levels.

Details

Homogeneity of slopes and homogeneity of variance are both checked. If the p-value is significant for any of the interaction terms or Levene's test, then this means the assumptions are not met. HomogeneityOfVariance() and HomogeneityOfRegressionSlopes() functions are both used in the function implementation.

Value

A matrix with two rows. The first row specify what the values are in the second row. The second row: The first element is the formula used to evaluate p-value of interaction terms. The next elements are the p-values for each interaction term. Following the p-value for interaction terms is the formula used to evaluate Levene test. The next element is the p-value from the Levene test.

Examples

dependent.col <- c(10.1, 11.3, 12.1, 13.7, 14.2, 1.6, 2.3, 3.2, 4.1, 5.3)
independent.col <- as.factor(c(1, 1, 1, 1, 1, 0, 0, 0, 0, 0))
covariate.one.col <- c(1, 2, 3, 4, 5, 1, 2, 3, 4, 5)
covariate.two.col <- as.factor(c(1, 0, 1, 0, 1, 0, 1, 0, 1, 0))

inputted.data <- data.frame(dependent.col, independent.col, covariate.one.col,
                            covariate.two.col)

results <- CheckAllAssumptionsANCOVA(inputted.data, "dependent.col",
                                         "independent.col",
                                         c("covariate.one.col", "covariate.two.col"))

results

yhhc2/ancovall documentation built on Dec. 23, 2021, 7:19 p.m.