In general terms, covariates are characteristics (excluding the actual treatment) of the participants in an experiment. If you collect data on characteristics before you run an experiment, you could use that data to see how your treatment affects different groups or populations. Or, you could use that data to control for the influence of any covariate.
Covariates may affect the outcome in a study. For example, you are running an experiment to see how corn plants tolerate drought. Level of drought is the actual “treatment”, but it isn’t the only factor that affects how plants perform: size is a known factor that affects tolerance levels, so you would run plant size as a covariate.
A covariate can be an independent variable (i.e. of direct interest) or it can be an unwanted, confounding variable. Adding a covariate to a model can increase the accuracyof your results.
控制变量是在实验中一定要保证不变的量;协变量在实验中不一定要控制不变,或者无法使其不变,其改变对实验结果不是很sensitive,![](https://pic.jg.com.cn/img/pinggu/096bb8250568747470733a2f2f696d616765732e73717561726573706163652d63646e2e636f6d2f636f6e74656e742f76312f3466353639346334323461636138643466386536393139342f313430373735383338343139312d314456534c4f534b454f57513451584a4647364c2f6b6531375a77644742546f6464493870446d34386b446252456952586e654f5258585a716f31666c6b435955717378525571716272316d4f4a594b66495052374c6f4451396d58504f6a6f4a6f71793831533249384e5f4e34563176556235416f494949624c5a68565978435257344250753130537433544241555159564b632d48564938494f366258696a4a3846484e7457765958506d47653175713134425f74396d57677930494756656e524f314571456649563479554439704c3750432f616e636f76612e706e67a6c6f0ef31.jpg)