Check model assumptions
Value
A named list with one element per assumption checked
(linearity, independence, homoscedasticity,
normality, multicollinearity, outliers), each
containing assumption (character label), check (logical
or NULL), details (character), and
recommendation (character). An additional overall element
summarises the number of assumptions checked, violated, and satisfied.
Examples
# \donttest{
model <- tl_model(mtcars, mpg ~ wt + hp, method = "linear")
tl_check_assumptions(model)
#> Registered S3 method overwritten by 'car':
#> method from
#> na.action.merMod lme4
#> Model Assumptions Check Summary:
#> --------------------------------
#> Linearity: VIOLATED
#> Details: RESET-style test on powers of the fitted values: p-value = 0.002042
#> Recommendation: Consider non-linear transformations or polynomial terms
#> Independence: VIOLATED
#> Details: Durbin-Watson statistic: 1.3624
#> Recommendation: Possible autocorrelation in residuals. Check for time-series structure or clustering.
#> Homoscedasticity: SATISFIED
#> Details: Breusch-Pagan test p-value: 0.6438
#> Recommendation: Homoscedasticity assumption appears satisfied
#> Normality of Residuals: VIOLATED
#> Details: Shapiro-Wilk test p-value: 0.0343
#> Recommendation: Residuals may not be normally distributed. Consider transformations or robust regression.
#> No Multicollinearity: SATISFIED
#> Details: Maximum VIF: 1.7666
#> Recommendation: No serious multicollinearity detected
#> No Influential Outliers: VIOLATED
#> Details: 6 influential observations detected
#> Recommendation: Consider inspecting observations: 16, 17, 18, 20, 29 ... (and potentially others)
#> $linearity
#> $linearity$assumption
#> [1] "Linearity"
#>
#> $linearity$check
#> [1] FALSE
#>
#> $linearity$details
#> [1] "RESET-style test on powers of the fitted values: p-value = 0.002042"
#>
#> $linearity$recommendation
#> [1] "Consider non-linear transformations or polynomial terms"
#>
#>
#> $independence
#> $independence$assumption
#> [1] "Independence"
#>
#> $independence$check
#> [1] FALSE
#>
#> $independence$details
#> [1] "Durbin-Watson statistic: 1.3624"
#>
#> $independence$recommendation
#> [1] "Possible autocorrelation in residuals. Check for time-series structure or clustering."
#>
#>
#> $homoscedasticity
#> $homoscedasticity$assumption
#> [1] "Homoscedasticity"
#>
#> $homoscedasticity$check
#> BP
#> TRUE
#>
#> $homoscedasticity$details
#> [1] "Breusch-Pagan test p-value: 0.6438"
#>
#> $homoscedasticity$recommendation
#> [1] "Homoscedasticity assumption appears satisfied"
#>
#>
#> $normality
#> $normality$assumption
#> [1] "Normality of Residuals"
#>
#> $normality$check
#> [1] FALSE
#>
#> $normality$details
#> [1] "Shapiro-Wilk test p-value: 0.0343"
#>
#> $normality$recommendation
#> [1] "Residuals may not be normally distributed. Consider transformations or robust regression."
#>
#>
#> $multicollinearity
#> $multicollinearity$assumption
#> [1] "No Multicollinearity"
#>
#> $multicollinearity$check
#> [1] TRUE
#>
#> $multicollinearity$details
#> [1] "Maximum VIF: 1.7666"
#>
#> $multicollinearity$recommendation
#> [1] "No serious multicollinearity detected"
#>
#>
#> $outliers
#> $outliers$assumption
#> [1] "No Influential Outliers"
#>
#> $outliers$check
#> [1] FALSE
#>
#> $outliers$details
#> [1] "6 influential observations detected"
#>
#> $outliers$recommendation
#> [1] "Consider inspecting observations: 16, 17, 18, 20, 29 ... (and potentially others)"
#>
#>
#> $overall
#> $overall$status
#> [1] "4 assumption(s) appear to be violated. See details."
#>
#> $overall$n_checked
#> [1] 6
#>
#> $overall$n_violated
#> [1] 4
#>
#> $overall$n_satisfied
#> [1] 2
#>
#>
# }