# Search results

1. ### Mistake in a textbook: What proportion of studies make "wrong" conclusions?

I only skimmed the OP and so won't comment directly on that, but rather on part of the idea that Bayesian statistical theory will replace Frequentist. I disagree with this because it implies the Frequentist theory is useless, which it clearly is not. I think you will still have universities that...
2. ### Is it necessary to check for multicollinearity of explanatory variables in logistic regression?

Also, multicollinearity might not be an issue even if it's present. If you're using the model for predictions, MC isn't necessarily problematic because it doesn't introduce bias into the estimation. However, if you're trying to make inferences on the beta parameters, then MC is more likely to be...
3. ### Is it necessary to check for multicollinearity of explanatory variables in logistic regression?

@hlsmith is correct: you are mistaken that multicollinearity is not something to account for in logistic regression. I also think for nominal variables you would check with collinearity with other variables (not necessarily dummies within the same variable being a problem, but you would expect...
4. ### F value help?

In general, test statistics (F, t, z, and so on...) should be referred to as "large" or "small" relative to the appropriate critical value. It may be small in absolute value, but if it exceeds the critical value, then the p-value will be smaller than the corresponding alpha level. I agree it...
5. ### Modeling cancer incidence rates

As far as the assumption regarding normally distributed errors, the provided histogram doesn't worry me at all. The sample size should also mitigate and "concerns" someone may have had. As for the other assumptions or just the overall appropriateness for your question, that is something you...
6. ### Frequentist v Bayesian

OH MY...”feelz...uncomfortable...sensitive...” :p
7. ### Frequentist v Bayesian

Essentially, Frequentist probability is about logic, and Bayesian probability is about feelz...powder keg in 3...2...1...
8. ### Modeling cancer incidence rates

Can you post a histogram of the residuals, also? I am not fantastic at normal prob plots yet, so it would help me look at the tails (and learn with real data). But I suspect it wouldn't be too great of a concern for the normality of error distribution assumption. What is the sample size?
9. ### Modeling cancer incidence rates

Actually, are all 3 plots of residuals?
10. ### Modeling cancer incidence rates

It is not generally true that a nonnormal Y variable necessitates nonnormally distributed errors. And sorry, before I somehow did not read that you said the residual plot provided. For the second part, I think “it depends” on a few things whether a count is reasonably handled by OLS in...
11. ### Modeling cancer incidence rates

Normality assumption refers to the distribution of the errors, not of the dependent variable. You should look into Poisson and negative binomial regression for rates.
12. ### What P value level do you suggest for this study?

Your approach is more aligned with the scientific process and with how p-values were intended to be used. I agree with you. I think part of the issue is pressure to publish but I think part of it is lack of understanding as I have seen firsthand. I literally had a well respected researcher...
13. ### What P value level do you suggest for this study?

The initial post was misleading then, as your wording asked if you should "...take them into consideration and report a marginally significant in a manuscript?" And so, I discussed the popular, but ill-conceived, idea about "marginal" significance (and the similar "trend toward" significance)...
14. ### What P value level do you suggest for this study?

There is no such thing as "marginally" significant. This is a term used by researchers in an attempt to paint nonsignificant tests as more favorable. Same goes for the bs term of "trending toward significance" for non significant test outcomes. A test of hypothesis is significant or it is not...
15. ### measuring student proficiency

If you would like help with homework, please provide your attempted solution.
16. ### Research Problem - Subtle Differences, is it significant?

I would suggest using maybe, 5 different versions at first with distinct, general themes or attributes and make adjustments off of that. Also, "enough statistical power and N is large enough..." is a vague statement that isn't really helpful. Are you going to randomize what participants can see...
17. ### Cox proportional hazard analysis - interpreting coefficients

Sorry- Hlsmith has the scale correct for this. I forgot the context and was thinking ordinary linear regression where, so he has the appropriate adjustment. I think there is a question, though about whether the scaling like that is appropriate because it seems you created a variable with so few...
18. ### Cox proportional hazard analysis - interpreting coefficients

In a way, I think these will still be on the ratio scale. They're ordered, differences of 20% (for example) are the same at any point, true zero exists, and 40% is twice 20% and 80% is twice 40%. Maybe the issue arises due to forcing limited responses, so measurement error is larger in the...

:rolleyes:
20. ### Random assignment

They have tables for random numbers if you don’t have excel. I just don’t see any reason for using the original method. Even a coin flip would be better.