Recent content by ondansetron

  1. O

    95% CI for rare incidence rate increasing in time.

    Yeah, the reviewers comment doesn't make sense to me because you're just plotting these separate intervals against time to show a trend. Their comment might be more valid if you were creating one CI for the entire time period (since your chart shows the rate may not be constant over the entire...
  2. O

    95% CI for rare incidence rate increasing in time.

    If you bootstrap and get really similar results, you could maybe use this to convince the reviewer that the constant rate assumption isn't violated in a material way, or isn't violated to begin with (I do agree with you that within each year, the constant rate assumption isn't necessarily...
  3. O

    95% CI for rare incidence rate increasing in time.

    You could try to bootstrap each interval at different time points to see how much the constant rate effects your estimates. Also, couldn't you just include a measure of time in the model and then use a time by x-variable interaction to account for the changed relationship over time (assuming you...
  4. O

    Which statistical test to use

    Why are you here, then? I'd imagine some people are here because they like tutoring, some people know quite a bit in some areas but not in others, some people may be brand new or just looking for homework help. I wouldn't say that anyone on the site necessarily lacks understanding, especially...
  5. O

    Probability of regression result

    You probably also need to account for autocorrelation of errors if the experimental unit is a unit of time, which it sounds like the case. Without this the estimates may be incorrect. I would also be careful of misinterpreting a CI or PI as a "95% probability" interval.
  6. O

    Comparing correlated data

    You quoted my post where I said absence of MC is not an assumption, then you went on to say you can't agree-- seemed much like you were saying you disagree and that absence of MC is an assumption. Maybe I misunderstood that part. If you reread post #3, you'll see that I'm clarifying for OP that...
  7. O

    Comparing correlated data

    I have at least one book that used no perfect collinearity as an assumption, granted it's an econometrics book by Wooldridge... I wonder where he got that as an assumption-- my guess would be the linear algebra degenerate matrix part. I always learned that there are essentially 4 assumptions in...
  8. O

    Comparing correlated data

    I appreciate your disagreement, but it simply isn't an assumption that's required or even made for analysis but relaxed in practice. The assumption is regarding perfect collinearity. You're correct that imperfect MC might lead to inflated standard errors, but that's not always a concern. In...
  9. O

    Anova

    For 2 I need to know what FDATA means in this case.
  10. O

    Anova

    What is "FDATA" mean in #2? Then maybe I can be more sure what they intended with the question. For#3 I'm fairly certain there is a typo and "two tailed test" should be choice D. What can you find in your notes or textbook regarding the "tailedness" of an F-test? What is the definition of a...
  11. O

    Comparing correlated data

    Absence of multicollinearity is not an assumption for something like ordinary least squares linear regression. The assumption is absence of perfect collinearity between independent variables, as this brings up issues regarding unique parameter estimates (and general fitting of the model). I also...
  12. O

    Anova

    Hi! We're happy to help. First, tell us what you think the answer is for each question and why that is the correct answer. Then, we can go about helping you arrive at the correct answer and explanation. #2 appears to be missing information in the question stem since it ends with ":" and isn't...
  13. O

    Time dependent COX analysis interpretation

    In my opinion, you should report all analyses done to give full disclosure in the paper. In you situation, you'll be able to report that the PH assumption was violated for a some covariate. You can then show the original model coefficients with p-values and CI for the coefficients, and then you...
  14. O

    Time dependent COX analysis interpretation

    I think that Staassis may have provided an answer that is better suited for a different question (assuming that his or her reply is regarding your cov*time interactions). If you've identified that the proportional hazards assumption is not reasonably satisfied in your case, you shouldn't be...
  15. O

    SPSS - significance of predictor when controlling for other predictors

    The t-test for that coefficient can answer that question, but it will account for all other variables in the model beyond status. If you only want to account for status, then fit a model with only intelligence and status. Just keep in mind this may be inappropriate and may lead to invalid...