Linked Questions

8 votes
2 answers

Does introduction of new variable always increase the p-val of existing ones?

I am doing some work that requires some estimates of gasoline oil demand elasticity on certain countries. After doing various econometric measures such as instrumental variable, I was able to get ...
The One's user avatar
  • 275
81 votes
0 answers

How can a regression be significant yet all predictors be non-significant? [duplicate]

My multiple regression analysis model has a statistically significant F value however all beta values are statistically non-significant. All the regression assumptions are met. No multicollinearity ...
Serene's user avatar
  • 811
2 votes
2 answers

Categorical variables in multinomial logistic regression end up converted into binary variables

When I run multinomial logistic regression with some of the explanatory variables as categorical, my algo (glm) turns them in binary variables, automatically. For examples if one categorical variable ...
Raghvendra's user avatar
3 votes
1 answer

Not-significant F but a significant coefficient in multiple linear regression

I have a regression with two continuous predictors and one dichotomous predictor in Model 1 and two interactions of each of the continuous predictors with the dichotomous predictor in Model 2. The ...
Nell's user avatar
  • 31
3 votes
1 answer

If the f-test is insignificant but coefficients are significant, can I use it?

If the linear regression's f-test is insignificant but its coefficients are significant in t-test, can I use this regression and its coefficients? In academic journals, I find people use linear ...
Eric's user avatar
  • 466
1 vote
1 answer

How to explain significant correlation between independent and dependent variable but non significant regression test in the presence of mediation? [duplicate]

Possible Duplicate: Not-significant F but a significant coefficient in multiple linear regression In my research, I use Optimism as the IV, Job Satisfaction as the DV and Work-Family Enrichment ...
too's user avatar
  • 11
6 votes
1 answer

Insignificant F-test in linear regression - when to stop?

I repeatedly read that one can stop looking further when the F-test is insignificant for linear regression; for example in the comments here. However, according to this very insightful answer only ...
mirei's user avatar
  • 63
4 votes
0 answers

Non-significant group effect, but LSD post hoc is significant. Why? [closed]

I am performing repeated ANOVAs in SPSS and came across something I don't understand. Basically, the main effect of group (I have three groups) is not significant (p = .062), but the LSD post hoc ...
Alexandre's user avatar
6 votes
2 answers

Why do my (coefficients, standard errors & CIs, p-values & significance) change when I add a term to my regression model?

Lots of people seem to be asking this. They often seem to get shallow answers that merely assert what is true, instead of drawing or explaining the mechanism. They also seem to not find each other -- ...
eric_kernfeld's user avatar
6 votes
2 answers

Is it possible to simultaneously call multiple regression coefficients significant?

Okay, this is a thought experiment: Suppose you have a dataset with 40 covariates. Suppose the data has every nice theoretical property you could want: randomly sampled, variables not correlated, etc....
user avatar
1 vote
1 answer

Significant coefficients but non-significant likelihood ratio test [closed]

Following a comment on this thread, I have a question about interpreting a logistic regression model with significant coefficients, but non significant likelihood ratio test. I have a super simple ...
becbot's user avatar
  • 91
2 votes
0 answers

Could removing variables improve model prediction?

Coming from a machine learning background, I have long held the idea -throw in all variables and let regularization and cross validation fight against over-fitting. The reason I am posting this ...
denizen of the north's user avatar
0 votes
2 answers

Factors a, b and c walk into a regression ... (multicollinearity puzzle)

I have three factors a, b, and c. In the three univariate models y ~ a y ~ b y ~ c a and ...
enfascination's user avatar
3 votes
0 answers

If you know a factor is significant, what is a reason why R might think it's not? [duplicate]

I'm running a logistic regression model where anecdotally I expected age to be a very large factor. If you see from the charts I made in Excel before running the model through R, this is how the ...
Ryan's user avatar
  • 303
1 vote
1 answer

Interpretation of results of a regression analysis

Here're the results of a multi-variable regression analysis run by Stata to test the effects of the three factors on the price elasticity of supply, which is the dependent variable. The coefficients ...
Joanna's user avatar
  • 11

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