Recent content by kiton

  1. kiton

    Seeking advice on 3-level HLM

    As it turns out, the case I am observing with my data is related to the estimation of cross-level effects in multilevel models. For those facing challenges similar to mine, I recommend a great paper by Aguinis, H., Gottfredson, R. K., & Culpepper, S. A. (2013). Best-practice recommendations for...
  2. kiton

    Seeking advice on 3-level HLM

    I keep thinking about the issue in hand and here are some additional elaborations. Given the structure of the data: Level 1: Individual reviews — includes user ratings and duration of use Level 2: Products — includes expert rating Level 3: Product categories Rule #1 in HLM is that outcome is...
  3. kiton

    Controlling for response bias where all goals are positively related to well-being: regression or mean-centering?

    Thank you for a good question. Although I am not an expert in response bias, here some of my thoughts about this. Response bias could be driven by the following: people are inclined to say “yes”, people act differently when they are taking part in research, some people tend to use extreme ends...
  4. kiton

    Panel regression: Deciding on fixed effects and random effects - Hausman

    I will suggest reading the following note by Richard Williams.
  5. kiton

    Seeking advice on 3-level HLM

    No red flags, nothing? :)
  6. kiton

    Seeking advice on 3-level HLM

    Hello! I am studying the association between product quality measured by expert intermediary (overallScore) and that measured by online user rating. In particular, I hypothesize that the aforementioned association is dependent on the longevity of product use. For instance, I would expect a...
  7. kiton

    Control variables vs mediated moderation?

    Are you asking because your experiment results don't hold with added controls? If so, perhaps you should look deeper and try to understand which specific control(s) influences your estimated interaction coefficient. On a side note, what's your sample size?
  8. 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)...
  9. 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.
  10. 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...
  11. 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...
  12. 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...
  13. 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...
  14. 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...
  15. 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...