# Tag Info

### Regressors Became Statistically Insignificant Upon Correcting for Autocorrelation

One possibility is that both your dependent and independent variables are related to time. This is the source of many humorous correlations such as: Ice cream sales go up when sharks attack or ...
• 125k
Accepted

### How to do maximum likelihood estimation when numerical derivatives cannot be calculated

There are optimisation algorithms that don't require derivatives. You can divide them into algorithms that assume derivatives exist but don't require them algorithms that don't assume smoothness A ...
• 41.6k

### Cannot seem to find a statistical difference despite a clear difference in the dataset

I tried to replicate @dimitriy's results in Python and got slightly different results: ...
• 9,418

### Cannot seem to find a statistical difference despite a clear difference in the dataset

You can detect a positive additive effect of both surgical and endovascular, though not surgical on its own. Jointly, both effects are marginally significant. These effects are relative to just ...
• 37.3k

### Regressors Became Statistically Insignificant Upon Correcting for Autocorrelation

Autocorrelation Influences My answer is a bit of a two-parter, the second part largely being more important than the first. First, a bit about autocorrelation... Consider the following data that I ...
• 15.9k
Accepted

### Interpreting a coefficient of a predictor not involved in an interaction term in a linear regression model with an interaction

As age is continuous, you would interpret the coefficient as all other variables kept constant, a one year increase in age leads to a 0.0488 unit increase in bmi.
• 56
Accepted

### Diff-in-diff with an unbalanced panel

With this kind of attrition, the bias will make the effect less negative, making the medication seem less effective at lowering BP. If the effect remains significant, you can say that with this kind ...
• 37.3k
Accepted

• 41.6k

### US states - fixed or random effect?

Random effects are best used when you are trying to summarize a lot of variation between groups, people, or any other cluster of data (see lengthier discussion here). In this case, 50 clusters (states)...
• 15.9k

### Understanding differences in collinearity across Stata commands

reghdfe is different because, by default, it tries to deal with collinearity. I don't have Stata, but a little Googling found pages about this. It should be in the documentation for the program. The ...
• 125k

### Multivariate Analysis for Personal Hygiene Product Survey

This is a tricky quant marketing problem with multiple complications. I am not aware of an easy solution. But I will try to outline how I think about the problem to point you in the right direction. ...
• 37.3k
1 vote

### statsmodels: Update OLS' degrees of freedom when absorbing 3+ fixed effects

In R, the following correction restores equality of the (nonrobust) s.e.s of the residual-based regression to the fixed-effects based ones: ...
• 34.2k
1 vote

### About regression analysis with categorical variables

This really depends on what your research question is. If you're simply interested in the effect of the continuous variable, you can just run a regression and look at the Wald test for the coefficient....
1 vote

### When I am comparing RMSFE between a log model and a level model of the same dataset, how should I proceed?

It is much easier to keep the AR(2) forecast, which is already on the original scale, and transform the AR(5) forecast from the log scale to the original scale. However, simply taking the exponential ...
• 127k
1 vote

### High t statistic with high p value for same variable?

Your standard error is adjusted for only 2 clusters. That doesn't look right. It's hard to find a definitive answer to the minimum number of clusters (the book 'Mostly Harmless Econometrics' suggests ...
• 18.3k
1 vote

### Interpreting Significant Interaction Term Odds/Hazard Ratio with Binary Variables

See https://stats.stackexchange.com/a/636401/4253 which is not written for any particular model such as the Cox PH model, but works generally.
• 95.8k
1 vote

### any problems with Firths Logit model (to deal with separation)

Partially answered in comments: No time to provide an elaborate response, but Greenland recommends log-F(1,1) prior instead of Firth's bias correction method. And you can implement it by simply ...

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