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  1. kiton

    Healthcare vs. education: interpretation of the findings

    Hello everybody! So I came across two studies that test a similar model of reputation and its impact on financial performance in the contexts of US business schools and cancer-treatment hospitals. In case of business schools, while the impact of prominence (think top of mind awareness)...
  2. kiton

    Modeling cancer incidence rates

    I apologize for such a late response, was gone for a while. The residual histogram is attached. Sample size is 2,500 US counties observed over 3 years.
  3. kiton

    Modeling cancer incidence rates

    Your argument is surely correct. It's just somehow this is a relatively common scenario in my field. Okay, I understand that if a count is reasonably handled by OLS in comparison to Poisson and NB, then it's plausible to use OLS for a count outcome. Let me double-check though if the same holds...
  4. kiton

    Modeling cancer incidence rates

    Thank you for response. That's absolutely correct, and that's exactly why I include a residual plot to assess the model fit. Relatedly, if the outcome's distribution is abnormal, residuals would not be "normal" either. Let me ask a clarification question on the second part though. If I were...
  5. kiton

    Modeling cancer incidence rates

    There is an interesting article on the topic -- Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002). The importance of the normality assumption in large public health data sets. Annual review of public health, 23(1), 151-169. But I feel I am too old school and still believe in BLUE for...
  6. kiton

    Modeling cancer incidence rates

    Hello dear forum members, Using county-level panel data (N = 2500+, T = 3) I aim to examine the associations between multiple biological, socioeconomic, and psychological factors and cancer incidence. There are two outcome measures available for me: (1) cancer incidence rate, IR = (New cancers...
  7. kiton

    What to add to Binominal Regression? Demographics + motivations?

    If your theory (or common sense) says that those predictors are relevant to predict you outcome, then add them in the model (regardless of significance of their impact or percent of variance explained). In terms of order, I typically include the focal predictor in the last place (although in...
  8. kiton

    What is the appropriate model?

    The correlation of .4 does not seem to exceed the commonly used threshold of .5 (at least in my field -- MIS). Therefore, I wouldn't be concerned about it. To obtain additional evidence that collinearity does not have a negative influence on your estimates (CIs, technically), you can run a...
  9. kiton

    Univariate Logistic Regression - how to performe

    Univariate analysis implies that you have a single dependent variable (multivariate, in contrast, assumes >=2 outcome variables). Based on your description, your analysis is univariate -- given a single binary outcome. It seems to me that the reviewer implies a case, in which you include...
  10. kiton

    "Quartile" Regression

    hlsmith, thank you for the hint. I believe I was able to accomplish the task. In particular, I created two dummies that equal 1 if an observation fell in the lowest or highest quartiles, respectively. I than used each of these dummies as predictor in the model. The estimated coefficients, their...
  11. kiton

    "Quartile" Regression

    hlsmith, I appreciate your response. Let me look into piecewise regression. It seems that a single model with indicators could be the way to go.
  12. kiton

    "Quartile" Regression

    Hello dear forum members, I am conducting a replication study based on the paper by Gao, G. G., Greenwood, B. N., Agarwal, R., & McCullough, J. S. (2015). VOCAL minority and silent majority: How do online ratings reflect population perceptions of quality. MIS Quarterly: Management Information...
  13. kiton

    Unusual distribution of the continuous outcome

    On a side note, it seems to me that Finite Mixture Models (FMMs) could be applicatable to the case of my initial outcome (amp).
  14. kiton

    Unusual distribution of the continuous outcome

    Yes, the latter two plots are quantiles of residuals against quantiles of normal distribution. Here is the historgram of the residuals: It seems to me that the model is failing over the small AND large values of the outcome (i.e., those that are about 2SD below and above the mean). My DV is...
  15. kiton

    Unusual distribution of the continuous outcome

    Dear Miner, hlsmith, thank you for your advises. Here is how I addressed the aforementioned issue. Following Miner's suggestion, I firstly experimented with various clusters. However, the result (as well as the model fit) were not appropriate. Then, given that I have two variables -- (1)...
  16. kiton

    Unusual distribution of the continuous outcome

    Does quantile regression approach sound plausible? Given the abnormal distribution of amp, I can explore the impact of predictor at different portions of the amp's distribution (i.e., 50th [given median is half the sample], and then 60th, 70th, 80th, 90th, and 95th [given the "groups" observed...
  17. kiton

    Unusual distribution of the continuous outcome

    Miner, thank you for your response. Indeed, these are groups and I have investigated those. Let me clarify. Average Medicare payment (outcome) is calculated based on the HCPCS codes (these identify different procedures conducted by the doctors). Since there are many different procedures, they...
  18. kiton

    Unusual distribution of the continuous outcome

    spunky, thank you very much for your advise. I will explore gamma reg (by the means of GLM I'd assume) in greater detail.
  19. kiton

    Unusual distribution of the continuous outcome

    Thank you for response, hlsmith. When I transform amp using natural log, the estimates are consistent (histogram is not good). However, the residuals are still "bad" (although the model fit in terms of R-squared goes up from .2 to .32). Following are the three plots (quantiles of residuals...
  20. kiton

    Unusual distribution of the continuous outcome

    Hello dear forum members! I am seeking your guidance with the following issue. So, I am estimating a "classic" difference-in-difference model (using pooled OLS estimator): Y = time + treated + time*treated, where Y is the average Medicare payment (amp) in $. Here is the descriptive...