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  1. hlsmith

    Predicting treatment outcome analysis

    Statistics don't know directionality, that should be your content knowledge. So once you, decide which direction you are examing, tell us more about the variables and sample size.
  2. hlsmith

    profits in Classification trees

    So individual regression trees or random forest? Post 6874975075 along with questions!
  3. hlsmith

    Economics - Instrumental Variable: Does including past values of regressors into the IV cause exogeneity assumption to fail?

    I apologize that this not my forte at all, but I find such topics interesting - so I will see if I can help. Do you only have a value for Y for one cross-section of time? Otherwise if you have historic Y as well marginal structural models can be use to control for time-varying confounding. Or...
  4. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    A 1% increase in exogamy is associated with an expected 1.11 times greater relative hazard for extinction. As @ondansetron mentioned, you would have to think about if it is appropriate to examine a 1 unit increase given the sparseness of simulated values. The above values I estimated would...
  5. hlsmith

    How can be used time series in sport?

    Anything recorded could be plotted. Say if you were modeling American college football wins (yes/no), many large programs play smaller schools early in the season. So you would imagine to predict wins early in the season based on prior year's data since playing smaller schools is a 'seasonal'...
  6. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    1% increase based on each category: 20% 1.129 40% 1.122 60% 1.107 80% 1.109 100% 1.200 I wasn't expecting that to be as consistent, but perhaps it is an artifact of the data being synthetic.
  7. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    The down scaling of the HR is likely: exp^(coef * 0.05) For fun, you could repeat this for the different comparisons and see how close the estimates are. The above is for 20 versus 0. For 40 versus 0 it would be exp^(coef * 0.025)
  8. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    PS. I don't use PHReg much but there are model assumption (e.g., proportional hazards) that need to be tested.
  9. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    Well, since you have created 0% and 20% categories and we treated it like a group, we need to be a little careful with interpretations. If I had to articulate it I would say, Based on agent based simulations, the population with 20% exogamy had an 11.4 (95% CI: 11.3, 14.7) times higher hazard...
  10. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    I would enter the variable into the model as categorical variable then select one group as the reference group, either the 0 or 100%. Then you will get relative hazards in comparison to the reference for the 4 other groups, so 4 coefficients. If the outcome is extinction, then your coefficient...
  11. hlsmith

    %INCLUDE statement error

    what documentation, provide link. Not an area I am overly familiar with, but your first line has quotes and second doesn't. Also, in first line the full text is not in the quotes?? But not my area as noted.
  12. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    Yeah, a couple of concerns I had were the linearity and then the covariates distribution. Is it appropriate to say a 2 unit increase follows a linear relationship true to the 1 unit increase? And also, if so, are all of the values cluster to certain values or are they dispersed? Ideally, you...
  13. hlsmith

    Cox proportional hazard analysis - interpreting coefficients

    What program are you using and can you post the output (results) from the program exactly as they were generated? Did you call the predictor a continuous variable? It seems like ordinal categories. Can you also post a histogram of the variables distribution? It is likely if you enter it as a...
  14. hlsmith

    How to find similar expression profiles within a table

    I would guess people may not have followed you context description. So you are trying to see if cell markers (binary: yes/no or continuous?) effect a classification (binary: Yes/No or continuous?)? Are there any feedback loops?
  15. hlsmith

    Multiple comparisons to a reference value - which test?

    Yeah, I was just referring to having an a priori plan, so that you don't end up selecting the correction that serves your hypotheses best after running a couple of different ones. I am sure you know this, I just try to hammer it home over and over again since it is a contributor to the...
  16. hlsmith

    Multiple comparisons to a reference value - which test?

    Conservative means fewers false positive and erring on the side of caution. You should pick one before ever applying it otherwise you bias things. Benjamini-Hochberg is popular as well.
  17. hlsmith

    Average marginal effects in logit model

    Now X1 has three levels. Post your figure if possible, It may need confidence intervals. You will also need to slap confidence intervals on the RERI if you got that route.
  18. hlsmith

    Difference in differences estimation using a regression

    I don't have much time, so I will direct you to a paper that I like on the topic: "How D-I-D you do that? Basic difference-in-differences model in SAS" by Warton et al. Ignore that it is in SAS, the concepts carry over.
  19. hlsmith

    Multiple comparisons to a reference value - which test?

    You would likely use the same ol' test you normally would, but repeat it for the number of categories you have. You then adjust your alpha (level of significance) with whichever correction you want. The most common is Bonferroni. So given that correction you would change your alpha cut-off to...
  20. hlsmith

    Analysis of case-control

    I historically get confused by terms "conditional / marginal". I think it is because they are never defined in complex settings. I was under the idea, conditional would come from the model controlling for covariates and marginal would come from an empty model like yours. What are you looking...