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  1. ondansetron

    Likert scales

    TO: DarioMarenelli This is why we ask questions... Finding them on EFA doesn't make them real, they very well can be spurious covariance structures, so context is needed, even in exploratory. Give some examples of statistical analyses that don't need context. You also used ad hominems on...
  2. ondansetron

    Likert scales

    @Karabiner asked fair questions. Typically people conflate Likert items and scales and most people who think they're using these are actually using Likert-type items/scales because they don't meet the theoretical requirements of true Likert items/scales. Getting defensive about your knowledge...
  3. ondansetron

    Residual sum of square

    This is, as @hlsmith said, a moot point. It's illogical to compare models with different dependent variables, generally speaking. Weight in grams is a different DV than weight in kg (even though it is a transformation), and only RSS should be compared from the same DV, but even this is missing...
  4. ondansetron

    Bonferoni test

    What do you believe "significance" means?
  5. ondansetron

    Bonferoni test

    This is a pretty useless thing to explain, in general. P-values have limited information to convey and it's a misconception that "significance" is some targeted endpoint with tons of value. It also sounds like in your OP that your goal is to have something be significant since your concern is...
  6. ondansetron

    Bonferoni test

    Just reposting this because anyone who reads now in the future should see the emphasis that p-values tell you nothing about "A is quite better than B."
  7. ondansetron

    Comparing withdrawal rates for a course

    I'd probably also look for a CI method that preserves the nominal coverage. For a difference in two proportions, I believe the Agresti-Caffo method is a good option and if just trying to get a CI for each proportion, then the Agresti-Coull method is a good choice (but there are others with...
  8. ondansetron

    Confidence interval in inter-rater reliability

    Depends on the underlying sampling distribution...if it's asymmetric, you get an asymmetric CI.
  9. ondansetron

    Omitted variable bias

    1) I disagree here, and Harrell makes a case for this when he points out that if you dichotomize a continuous independent variable, you can reduce confounding by also including the original continuous variable. 3) I assuming linearity, it wouldn't look different than a two variable interaction...
  10. ondansetron

    Omitted variable bias

    I think confounding and OVB at least can be the same, if they are not always the same. The first example I learned about a fractional factorial experimental design, the guy teaching it (PhD in Stats from a good program along with decades of consulting), he explained a fractional factorial as...
  11. ondansetron

    Can I set the breakpoint of piecewise regression by theoritic reference?

    For the first just model SBP as a function of the raw BMI values (possible with a transform to make SBP nonlinear in BMI (SBP doesn't increase infinitely with BMI). For "want to show yearly increasing SBP&BMI..."? Can you reword this, I'm not quite sure I understand what you mean.
  12. ondansetron

    Can I set the breakpoint of piecewise regression by theoritic reference?

    No, breakpoints in clinical medicine are generally nonsensical despite their widespread use and "acceptance". BMI is a continuous variable and patients in the arbitrary WHO guidelines have very different risk profiles, even within the same category. SBP likely doesn't "jump" between categories...
  13. ondansetron

    Linear mixed model? Please help meee!

    Can you be more specific? 1) What is it? 2) What does fixed effect mean? 3) What does random effect mean? 4) How is this different from a "regular" linear model? 5) What are the assumptions of a linear model? 6) What are the assumptions of a linear mixed model?
  14. ondansetron

    Linear mixed model? Please help meee!

    To avoid telling you answers, I like to ask questions that make you find the answer :D 1) What is a linear mixed model? How is it different from a regular linear model? What are the assumptions needed for each? 2) Worry about this later. Generating output is the easiest part of statistics...
  15. ondansetron

    Age-adjusted P value

    It is generally inappropriate to employ p-values when looking at baseline characteristics.
  16. ondansetron

    5 year average data- statistically significant increase?

    This leads me further down the path: why is it that you want to report significance? What does significance and a p-value mean in your perspective (i.e. practically and definitionally)? Small numbers of events aren't necessarily and issue. But I think hearing your answers might provide insight...
  17. ondansetron

    5 year average data- statistically significant increase?

    To best help and provide advice, as @Karabiner has started to do (and question), would you explain what you know about p-values and why that is your proposed solution to answer this question?
  18. ondansetron

    Comparing F-statistics

    When doing a MANOVA, you want to consider which omnibus test might be best for your situation. It's possible one or more is most ideal based on it's performance characteristics, so you would look at the one/few you preselected. Do some research on when to use Pillai's trace vs Wilk's Lambda and...
  19. ondansetron

    Please solve my problems with difference between discrete and continuous variable.

    In the physics example, they're no longer measuring color, but wavelength which is a property of an electromagnetic wave whereas color is the perception of that phenomenon. The perception of color is nominal unless you're changing your variable to the perception of wavelength or using color as a...
  20. ondansetron

    Please solve my problems with difference between discrete and continuous variable.

    They are absolutely applicable terms for discrete variables. The number of students in a class is a perfect example of ratio-level measurement. Zero indicates no students in the class, a true absence of students. 10 students is actually half as many as 20 students. The difference of 15 and 10...