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  1. noetsi

    Wage project

    Its not a sample. It is everyone we are rated on for the federal government the entire population we deal with. Our data runs only right now into 2020 so it is not entirely clear if covid effects it or not. That is something I can look for, segmented regression maybe with the intervention in...
  2. noetsi

    IBM SPSS Statistics Viewer Error

    Change the directory where the software is pointing to. Or move the file.
  3. noetsi

    Wage project

    I am starting a new project and I want to get it right - it is the first we have run in many years and it covers a very important issue. I work for a public agency getting those with a disability jobs. Essentially we are looking at wages two quarters after people leave our agency as the...
  4. noetsi

    proc plm

    You are loosing it bot
  5. noetsi

    Different results when changing the reference group in logistic regression

    Well they might not. People get confused in SAS on this issue because they don't realize when they build dummy variables sas defaults to effect coding for the slopes, but uses reference coding for the odds ratios. Dummy variables are being compared to the intercept so if the intercept changes...
  6. noetsi

    Different results when changing the reference group in logistic regression

    I can't see the attachments so others probably can not either. Did you look at the SPSS documentation? In SAS dummy variables are tied to effect coding not reference coding and the OR are tied always to reference coding. SPSS, which I don't know, may do the same. So that is a place to start...
  7. noetsi

    Lasso regression

    SBC is BIC which I think stands for Bayesian Information Criterion Most of the book was beyond me, but I figured it would be useful to others. I did find some of the early stuff useful. I am not sure what you mean by this Next you have to stumble onto their book statistical inference in the...
  8. noetsi

    Relative impact

    A really interesting review of this topic. It is very discouraging to those like me who hope for a simple answer. Or really any answer. Grömping2015_WiresCS_AcceptedVersion.pdf (beuth-hochschule.de) As I review this topic I find several things. 1) There are many approaches to doing this. 2)...
  9. noetsi

    Lasso regression

    This is a very interesting monograph if I can get the paste to work SLS.pdf (stanford.edu)
  10. noetsi

    Lasso regression

    proc glmselect only runs linear models although for selection purposes my understanding is that does not matter. I decided the issue was the use of K fold validation which requires larger data sets than I have. So I tried using SBC as the criteria instead of validation. I got no warning this...
  11. noetsi

    Lasso regression

    randomdata is the half of the overall data I used to do lasso. Even when using the entire data set to do LASSO I get the following warning. WARNING: The adaptive weights for the LASSO method are not uniquely determined because the full least squares model is singular. and in the results I get...
  12. noetsi

    Lasso regression

    This is what I was going to do. But splitting the data in two this way leaves only about 224 non-missing cases of which only 24 are at one level of the DV. I don't think that is enough to actually analyze with the logistic regression. I am talking about the hold out data set used for that...
  13. noetsi

    Lasso regression

    It might be tied to this issue when I run logistic regression on the reduced data set used to choose the LASSO. This does not occur when I have the entire data set. But I split it into two pieces first to choose lasso variables. Then to run the logistic regression. I thought the whole...
  14. noetsi

    Lasso regression

    HLSMITH do you know what this means for LASSO and if its important? I think that always happens when you chose cross validation for LASSO, but I am not sure. Also if this warning matters for adaptive lasso/lasso. WARNING: The adaptive weights for the LASSO method are not uniquely determined...
  15. noetsi

    Multi-variate regression for a small sample

    I have solutions for SAS (and you can do them for R) but I have not used SPSS in many years. You want to look for non-linearity and heteroskedascity in your data by looking at the residual plots not a test. I am not sure what you mean by lie between .... See if SPSS does LASSO. If it does...
  16. noetsi

    Relative impact

    Anyone here familiar with dominance analysis? It seems like the right way to go after relative impact. One problem with relative impact is correlated variables (I assume they mean multicollinearity). I did a VIF test of the variables in my model and none were even 3 which suggests MC is not a...
  17. noetsi

    Multi-variate regression for a small sample

    37 is a really small sample. Particularly for 9 variables. Step wise regression is pretty much universally frowned on these days. The threads I did when I was learning Lasso this week show a much better approach (Lasso). They are not much harder than stepwise. You don't, in any case, use...
  18. noetsi

    Lasso regression

    hey hlsmith did I do this correctly. All the variables including the dummy variable have two levels. First I randomly split my data into two pieces. And ran this code ODS graphics on; proc glmselect data=randomdata plots=all; partition fraction(validate=.3); class pd1 pd2 pd3 pd4 pd5 pd6 pd7...
  19. noetsi

    can Multivariate normality avoid overfitting scenarios?

    Actually I meant to point out that multivariate normality, which means the normality of the residuals not of the predictors or dependent variable, is formally a requirement to estimate the standard errors (only it does not bias the slopes) but that if you have a moderate or larger sample even...
  20. noetsi

    Lasso regression

    I don't really understand the abstract, but this seems important. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties (princeton.edu)