https://mtaniguchiking.github.io/M4MD-forecast-docs-dev/tags/inference/Recent content in Inference on Models for missing dataHugoen-ushttps://mtaniguchiking.github.io/M4MD-forecast-docs-dev/posts/interpreting-coefficients/Mon, 01 Jan 0001 00:00:00 +0000https://mtaniguchiking.github.io/M4MD-forecast-docs-dev/posts/interpreting-coefficients/<h2 id="making-sense-of-the-effects-of-variables-included-as-predictors"> Making sense of the effects of variables included as predictors <a class="anchor" href="#making-sense-of-the-effects-of-variables-included-as-predictors">#</a> </h2> <p>Some aspects of covariate effects are readily apparent &ndash; for instance, the sign of a coefficient in a model says at least something about the general directionality of the effect, positive or negative. However, a deeper understanding of a model typically requires inferences that go well beyond simple measures of the <em>directionality</em> or <em>significance</em> of effects &ndash; it requires understanding the <em>size</em> of effects.</p>