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Covariate-Imbalance
Covariate-imbalance refers to the situation where the distribution of one or more covariates (variables that may affect the outcome of an experiment) is not equal between the treatment and control groups in an A/B test. This can lead to biased results and incorrect conclusions.
Impact on A/B Testing on Web and in Mobile
| Impact |
Web |
Mobile |
| Decreased accuracy of results |
Covariate-imbalance can lead to biased results and incorrect conclusions, which can decrease the accuracy of A/B testing on web. |
Covariate-imbalance can also lead to biased results and incorrect conclusions, which can decrease the accuracy of A/B testing on mobile. |
| Increased risk of false positives or false negatives |
Covariate-imbalance can increase the risk of false positives or false negatives, which can lead to incorrect decisions about website changes. |
Covariate-imbalance can also increase the risk of false positives or false negatives, which can lead to incorrect decisions about mobile app changes. |
| Difficulty in identifying the cause of differences in results |
Covariate-imbalance can make it difficult to identify the cause of differences in results between the treatment and control groups, which can make it harder to optimize website changes. |
Covariate-imbalance can also make it difficult to identify the cause of differences in results between the treatment and control groups, which can make it harder to optimize mobile app changes. |
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