Recent content by spunky

  1. spunky

    2 sample z test - Standardized Effect Size

    If you're assuming a Gaussian mixture then your answer is wrong UNLESS you further assume that the population means are zero. The general expression for the variance of a mixture is: \sigma^{2}=\sum_{i=1}^{k}p_i(\mu^{2}_i+\sigma^{2}_i)-\mu (where \mu is the grand mean of the mixture) So if...
  2. spunky

    Heterodastic thread on heteroskedasticity

    Well, the first part of my code has the DGP (Data Generation Process) so you can always reduce the simulated sample sizes to have a better look. Right now I'm doing 100 level 1 units (e.g. "kids") in 100 level 2 units (e.g. "classrooms") so if this were real data, my total sample size would be...
  3. spunky

    Heterodastic thread on heteroskedasticity

    What'cha mean by that? Like plotting the standardized/studentized residuals as opposed to raw residuals?
  4. spunky

    Heterodastic thread on heteroskedasticity

    Pfff... you're so right. I'm so dumb sometimes. Thanks for pointing it out!
  5. spunky

    Heterodastic thread on heteroskedasticity

    A follow-up the conversation that we were having. Basically, the idea that for a simulated, linear mixed effects model of the form Y = 0.5 + 0.5X_{1} + u_{0} + \epsilon_{ij} where u_{0} \sim N(0, 0.7) and \epsilon \sim N(0, 0.3) to get an intra-class correlation (ICC) of 0.7. ends up not...
  6. spunky

    Negative values in a Pattern Matrix after Exploratory Factor Analysis

    No. Corrected item-total correlations are.... well, that. You get the column of each item and correlate it with each sum score or average score or whatever way you're creating a 'score' in your scale. And they are "corrected" because the total score is calculated without the item you're...
  7. spunky

    Negative values in a Pattern Matrix after Exploratory Factor Analysis

    Care to elaborate on what this "Monte Carlo" is? Is this Horn's Parallel Analysis? This is weird because it honestly reads like a classic case of "oops, forgot to reverse code". If you run (corrected) item-total correlations treating each factor as an independent subscale, do you observe more...
  8. spunky

    Factor analysis with nested data

    Yes, you are violating a more general version of the assumption of heteroskedasticity. Because you have the same people responding to multiple surveys you have measurements (surveys) nested within respondents. For this kind of data you would need to perform multilevel factor analysis...
  9. spunky

    American Horror Story

    Is it good, though? Cuz I was a devout follower until Jessica Lange left. AHS-hotel with Lady GaGa just didn't do it for me :/
  10. spunky

    What is the best dip for tortilla chips?

    There is only one right answer to this question and that is GUAC. GUAC IS WACK.
  11. spunky

    relative impact of predictors

    I think I answered a question like this a while ago: http://www.talkstats.com/threads/variance-of-indivudial-variables-in-multiple-regression.71423/#post-206864
  12. spunky

    Hello from Washington, DC

    Hi! Welcome to our humble digital abode! We hope you'll have a great time here!
  13. spunky

    Frequentist v Bayesian

  14. spunky

    Frequentist v Bayesian

    I think in the main issue to keep in mind in the whole "Frequentist VS Bayesian" 2.0 debate (because it re-surfaces every time Bayes becomes popular) comes from the fact of how they conceptualize probability. For Frequentists, it's the long-run expected events / total sample size VS the Bayesian...
  15. spunky

    What does this F test nomeclature mean?

    It looks like the F-distribution from ANOVA (or regression, in this case) where the degrees of freedom of the model are the p predictors and the degrees of freedom of the error are sample size (n) - # of predictors (p)