Recent content by hlsmith

  1. hlsmith

    Normality: DV itself or residuals?

    It the residuals. Though its nice to know the distribution of variables you are working with. @Dason - can you send a link to you all's paper!
  2. hlsmith

    small sample size problems

    Is this a random sample and are users randomly assigned, are all of the comparisons planned, do multiple compasions/false discovery need to be controlled for? Quit encouraging this person. Yeah theoretically some things are possible, but should they be done and do they contribute to...
  3. hlsmith

    Comparing incidence rates

    Do you have raw data or just incident rates. The best approach is to calculate risk differences and control for repeated testing by correcting confidence intervals!
  4. hlsmith

    compare survival at a specific time point

    What terms are all in the model, and are you saying this is an SPSS issue?
  5. hlsmith

    when does multiple comparisons become a consideration?

    Yup, this is a big issue. Anytime you make more than one test you should correct even if you are comparing three groups to start with corrections are needed right then. It really is just that simple. If you are using an existing set you should set your level of significance low and make no real...
  6. hlsmith

    small sample size problems

    To put it another way, what do you hope to gain from comparing 1 vs 3, what would that contribute to your field?
  7. hlsmith

    Analyzing longitudinal unbalanced data - mixed effect quantile regression

    If i get a chance i will check out the attachments. Yes, i have seen quantile related approaches in STATA, since historically economists have used it. Good luck and update this thread along the way. I may need to one day figure it out. PS, I'm not a STATA user, most I'M mostly in SAS and R.
  8. hlsmith

    Analyzing longitudinal unbalanced data - mixed effect quantile regression

    Well a general rules says you may need quite a few groups to conduct MLM, say 70. You have many more. Next, I never recall how many within group points are recommended, but I would guess it is comparable to linear reg. A question for you, say you are able to run the MLM Quantile Reg model...
  9. hlsmith

    Help with interpreting log in regression

    B(lnGDP)2, is the two representing to the power of 2, e.g., 4**2 = 16?
  10. hlsmith

    Analyzing longitudinal unbalanced data - mixed effect quantile regression

    Have you ever conducted quantile regression before? That would be a first step. I have not run repeated measure quantile reg before, but I know it is an option. You have multiple observations, and this is why you want to do MLM correct? What do you mean by this, "not all companies have the same...
  11. hlsmith

    Multivariate regression on 11 patients

    You probably don't have enough data to power a simple linear regression and meet its assumptions, and definitely not enough to control for patient characteristics in the model. A general rule which may not always hold, is you need 10 or more outcome observations for each predictor. To put it in...
  12. hlsmith

    data transformation

    Not an area i am too knowledgable in, but i think you can request pdf specifically for normal, lognormal, and other distributions.
  13. hlsmith

    LASSO

    I didnt have time to go through the CHOOSE options, but this video seem fairly informative: https://www.coursera.org/lecture/machine-learning-data-analysis/testing-a-lasso-regression-with-sas-ntKNE I also saw that SAS seems to be catching up, they have a macro for group LASSO and incorporation...
  14. hlsmith

    LASSO

    I use r for it. But i would guess it uses Breiman's 1 SE rule, or you should select it. Which finds the best penalized model that uses the most regularized comparable model with the fewest terms (regularized). Frank Harrel gave a talk last week where he said everyone uses the defaults in LASSO...
  15. hlsmith

    Multivariate regression on 11 patients

    Can lactos e intolerance be considered a medelian randomization (instrumental variable)? However with 11 covariates things may still not be balanced. Why cant you have more subjects??