Regression - Diagnostic - Plot - Cook's Distance

A line/rug plot showing Cook's Distance for each observation fitted in the regression model.

Example

Sample output from plotting the Cook's distances for a quasi-Poisson regression model. No data points appear to be overly influential.

Details

Used to detect highly influential data points, i.e. data points that can have a large effect on the outcome and accuracy of the regression. For large sample sizes, a rough guideline is to consider values above 4/(n-p), where n is the sample size and p is the number of predictors including the intercept, to indicate highly influential points.

Acknowledgements

Uses plot.lm and/or plot.glm function from the stats R package.

References

Cook, R. Dennis (1977). Detection of Influential Observations in Linear Regression. Technometrics. American Statistical Association. 19 (1): 15–18. DOI: 10.2307/1268249.

Williams, D. A. (1987). Generalized linear model diagnostics using the deviance and single case deletions. Applied Statistics. 36: 181-191. DOI: 10.2307/2347550.

Fox, J, & Weisberg, S. (2011). An R Companion to Applied Regression. 2nd Edition. SAGE Publications. ISBN: 9781412975148.

Code

var __webpack_modules__ = ({});
// The module cache
var __webpack_module_cache__ = {};

// The require function
function __webpack_require__(moduleId) {

// Check if module is in cache
var cachedModule = __webpack_module_cache__[moduleId];
if (cachedModule !== undefined) {
return cachedModule.exports;
}
// Create a new module (and put it into the cache)
var module = (__webpack_module_cache__[moduleId] = {
exports: {}
});
// Execute the module function
__webpack_modules__[moduleId](module, module.exports, __webpack_require__);

// Return the exports of the module
return module.exports;

}

// webpack/runtime/rspack_version
(() => {
__webpack_require__.rv = () => ("1.7.2")
})();
// webpack/runtime/rspack_unique_id
(() => {
__webpack_require__.ruid = "bundler=rspack@1.7.2";
})();
includeWeb("QScript R Output Functions");

const menu_location = "Regression > Diagnostic > Plot > Cook's Distance";
createDiagnosticROutputFromSelection(menu_location);