logistical regresion

  1. O

    Does a reduced sample size after joining two datasets count as missing data?

    Hi there, I have two datasets both share names which is what I use to join them together to form my sample on which I am running a logistical regression. However, after performing a fuzzy join I only have about 55% of the data matching (5.5k out of 10k observations). Does this count as missing...
  2. L

    Average marginal effects in logit model

    Hi I have performed two logistic regression models (full model and stepwise reduced model). I have 8 predictors and 5 predictors, respectively. Both continouos and categorical predictors and binary outcome. Now I want to calculate average marginal effects, but will it only make sense to do it...
  3. D

    Which method? Categorical data (IV) and continuous numerical data (DV)

    Thanks in advance for taking a look at my query I have been trying to get some statistical support from my local research department but I am getting conflicting opinions on which statistical methods I should be using to analyse my data. Any thoughts or insights would be much appreciated...
  4. E

    Logistic regression using dummies with dependent "holes"

    Hi, I'm trying to do do a logistic regression using R. I want to regress using binary dependent variable Y as granted or not grated (1 or 0) using the model in the following way (just showing few covariates here): glm(Y ~ age + score + wage + employmenttype + co_person + co_score + ...
  5. D

    Logistic Regression: To dummy code or not to? Which backward elimination to use?

    I have 10 binary dependent variables (disease prevalence: yes/no, 1/0). I want to do a logistical regression with each of them with the following binary categorical independent variables: - Year (8 levels) - Gender (2 levels) - Age (11 levels) - Season (2 levels) - Location (10 levels)...