regression

  1. T

    Logistic regression in Stata with binomial dependent variable 3-level categorical predictor variable

    Hi, I'm doing a logistic regression analysis with a binomial outcome variable (Yes / No). My main predictor variable is categorical and has 3 levels. I'm also including categorical and continuous confounding variables as predictors. What is the best way to convert my outcome variable from...
  2. A

    How to interpret the intercept in a regression model which has a categorical covariate?

    I have a regression model with some response Y and covariates height, weight, age, sex. Sex is the only categorical covariate and it takes on the value Sex = 0, for female Sex = 1, for male I want to interpret the intercept of this model, that is the estimated mean value of Y when all the...
  3. A

    How to choose between two regression models when one has a higher adjusted R^2 and the other has a lower BIC?

    I have two regression models with different number of covariates/predictors. After performing a subset selection, the remaining two choices are Model 1, which has 7 covariates and a lower BIC. Model 2, which has 11 covariates and a higher adjusted R^2. Using the BIC criteria, you select the...
  4. M

    Replacing regressor instead of 2SLS

    Hi, can someone explain me why it is usual to run a 2SLS if we are not "satisfied" with one variable and using an instrumental variable to adjust the model? (I am just talking about the just-identified case) Wouldn't it be easier just to replace the variable with the new one, so we have a new...
  5. R

    Interpretation of interaction terms in a multiple linear regression

    I try to improve my statistical knowledge and right now I am working on a regression that contains interaction terms. I am currently investigating the effects of different variables (a1, a2 etc.) on the quantity of chairs sold in a transaction (dependent variable). To see if effects are...
  6. R

    Help to formally write down a linear regression

    Hello altogether, i am currently analysing a dataset of 10,000 transactions. I am analysing the effect of different advertising campaings on the quantity of chairs by using multiple linear regression model with zip code and day dummies. I am interested in formally writing the regression model...
  7. J

    IVs and moderator variables correlate in three-way interaction - problematic?

    Hi everybody, let's assume I hypothesize: H1: A direct effect of X1 on Y H2: A direct effect of X2 on Y H3: A two-way interaction between X1 and X2 H4: A three-way interaction between X1, X2 and X3 H5: A three-way interaction between X1, X2 and X4 and run the following OLS regressions to test...
  8. S

    Constant not sig. in multiple regression - does it matter?

    I did a hierarchical multiple linear regression in SPSS with three predictor variables. All the variables have high F-values and are highly significant at each step of the model, but the constant is not significant (0.079) in the last step. Should I disregard all the results just because of...
  9. S

    Regression Question for Measuring a Corporate Campaign

    Hi everyone, I hope you are all having a great day. Currently, I am trying to measure the effect of an in-store campaign that deals with sampling items. I have 80 stores (40 control and 40 test). I have many interesting variables, such as average local income, number of competitors within X...
  10. D

    What model should I use?

    I have a longitudinal survey (5 waves) that collects a health index (from 0 to 100) and some risk factors and socioeconomic characteristics. I want to develop a model that will predict this health index (with consistent biographies, meaning that the predicted health index should not be...
  11. G

    Random Regression in R

    I am a student. I have some knowledge of mixed regression models. I would like to implement Random Regression in R. I found "Random Regression Models" by Schaeffer (http://animalbiosciences.uoguelph.ca/~lrs/BOOKS/rrmbook.pdf) helpful. I have also read "MCMCglmm Course Notes" by Jarrod Hadfield...
  12. I

    Regression analysis across multiple data sets

    Hi All. I'm new to this forum but I have a background in stats and in business/social science research. I'm in the early stages of designing a research study that will analyze a large dataset for about 100 publicly traded companies. There will be about 10-20 independent variables for each...
  13. L

    Inverted U-shape estimation

    Hi, I am currently writing my master dissertation about the impact of corporate income tax reduction on the competitiveness of nations. It might be probable to assume that a reduction of corporate income tax will have a certain effect depending on the level of corporate income tax already...
  14. P

    Statistical Test for multiple choice questions

    I Iaunched a survey recently where I have the following types of questions - 1) A multiple choice question (where users can mark more than one correct answer), let's call it variable a. 2) A single choice answer type question (radio button type), let's call it categorical variable b. 3) A...
  15. G

    distance from expected in terms of standard deviations

    assume I am predicting home runs, assume all player bat the same number of times, so we can do this by total home runs, and not home run rate) from a player based on past experience. I have a linear regression model for one period of time that determines the model, and I then run 100 players...
  16. B

    Looking for the best way to use my available data in a predictive model

    I have several pieces of data available, but I'm not sure about the best use of it in a predictive model. I envision using a regression, then plugging the predicted values into a monte carlo simulation for optimization. I'm wondering how an experienced statistician would use the available data...
  17. M

    One predictor overshadows all other?

    Hi everyone! I was wondering, how do I deal with a predictor that overshadows all others? All predictors included in the model are statistically significant, but one of the has a very strong impact on the dependent variables, so much that when its value is high, the impact of all other...
  18. 0

    Comparing categories of a independent variable in logistic regression

    Hello, I have a doubt about the ways of comparing categories in logistic regression. I have 200 subjects with a dependant variable (positive/negative) and I want to test them with an independent variable (IV) of 4 categories (age). I am going to use a logistic regression, but when I do that, I...
  19. T

    Logistic Regression Stata: ommitted due to collinearity ?? Help

    Hi there, I'm an MSc student in Medical Entomology and I'm in the midst of analysing data for my final project write up. My project is assessing the efficacy of different insecticide treatments applied in experimental huts against malaria mosquitoes. Now my dependent variables are: mortality...
  20. L

    How can I compare the effect of different VI on my VD?

    Hi, I would like to compare the effect of different independent variables on a dependent variable. My VD is quantitative. I have 3 VI that are nominal: Valence (2 levels), Rhetorical orientation (2 levels), statement type (3 levels). It looks like that: In order to asses the influence of...