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In statistical models, confounding is said to occur when the apparent dependence of the response on a predictor is partially or wholly due to the dependence of both on a third variable not included in the model, or dependence on a linear combination of other variables included in the model. Confounding with a variable included in a model is often called multicollinearity. A synonym is *aliasing*, used in design of experiments.

0 votes

How to compare between two different propensity matching done on the same outcome and exposu...

In general terms, propensity score matching (PSM) should include all available covariates (excluding those creating logical fallacies) associated with the outcome (see for instance: https://rmdopen.bm …
Giuseppe Biondi-Zoccai's user avatar
0 votes
0 answers
34 views

How to reduce subjectivity in the Baseline Inequality Index for meta-analysis

I have recently come across an interesting means to appraise baseline differences in competing groups in clinical trials being pooled for meta-analysis: the Baseline Inequality Index. As far as I am …
Giuseppe Biondi-Zoccai's user avatar
1 vote

Collider stratification bias or index event bias

First you need to check whether such claims were due to ecological fallcy. Then this may be due to survivorship bias. Another major reason is the use of cross-sectional rather than prospective designs …
Giuseppe Biondi-Zoccai's user avatar
1 vote
Accepted

Using blocking in propensity score analysis?

I understand your concern as the scientific literature on propensity scores and blocking is difficult to search given that blocking is typically used after propensity score estimation. You basically …
Giuseppe Biondi-Zoccai's user avatar
6 votes

advantages and disadvantages of IPTW vs propensity score matching?

Despite some similarities, propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) behave differently, mainly because matching selects some cases/controls and discards ot …
Giuseppe Biondi-Zoccai's user avatar