regression assumption

  1. A

    How can I check model assumptions when all my residuals are zero?

    I'm doing a 2^4 full factorial experiment. I have 1 continuous response Y and 4 factors, each with 2 levels, yielding a total of 16 level combinations. The experiment is unreplicated and I have a total 16 observations, one for each level combination. The design matrix has only 1's and -1's...
  2. A

    heteroskedasticity

    can anyone tell me is this a plot of heteroskedasticity or homoskedasticity.
  3. G

    Variable as confounding if it influences other factors in opposite directions?

    I examine the relationship between population density (PD) and the insurance density (ID) taking into account different market exploitations (ME) of an insurance company in municipalities. The correlation matrix (Pearson) shows the following relationships (all high signifikant): PD vs. ID (-)...
  4. K

    [SPSS - Logistic Regression] Resolve the linearity of logit assumption

    I am running a logistic regression and my income variable violates the linearity of the logit assumption. It is not negatively effecting the goodness-of-fit statistics. I have transformed the variable into a log but that impacted the constant and made the odds ratio explode. When I square...
  5. D

    Checking homoscedasticity in repeated measures

    Hello, When checking the assumption of constant variance for repeated measures data, am I correct in thinking that the variance of residuals should be compared across entities (e.g. participants in my experiment), as well as across the levels of each factor (e.g. drug dose)? Thus, it is...
  6. L

    Non-linearity in OLS-Models, Multinominal Logit-Regression

    Hey there, I have a question connected to the Ols-Model in case of nonlinearity between parameters. What should be done if the assummption of Linearity in OLS-Model ist not fulfilled and there is an non-linear relationship between the used parameters? And my second question is if I can use...
  7. S

    Is there a need to include fixed effects when assessing multicollinearity VIFs?

    I am currently in the progress of performing multicollinearity diagnostics for a logistic regression model using tolerance and VIF calculations based on recommendations in Allison (2012) (Logistic Regression Using SAS: Theory and Application, Second Edition). In my model I include three sets of...
  8. A

    Outliers

    Hello there, I have data set of 5846 observations out of which 15 observations are outliers. I need to perform multiple linear regression which as I know is highly sensitive to outliers. Do I have to filter those 15 outliers out or they will not mess up my analysis, since the number of...
  9. C

    Regression analyses and mediation with not normally distributed control variable HELP

    I am measuring the relationship between an IV and DV and whether two other variables mediated/predicted this relationship. All are normally distributed. I also collected the 'age' of the participants as a control variable, which turned out to show two distinct sample populations (18-25, and 26+)...
  10. A

    Solution for Non-normally distributed data

    hello there, I am doing some statistical analysis on medical sample data. I need to need to find variables which influences the length of stay in hospital. I was panning to do collaboration analysis and stepwise model for detecting regression model. My data is nor normally distributed...
  11. A

    Rating and Votes for hotels - how to connect?

    Hello everyone, I have collected data on hotels, and I want to run some regressions on it. One problem appeared: I have average rating for each hotel and also a number of votes by which it was calculated. So it is clear that 2 hotels with different rating and different number of votes can...
  12. A

    Normality assumption for Regression

    I have an outcome variable that is composed of one item on a 3 point scale to assess participation (none-1, member of 1 program-2, member of both programs-3). n=766 The test for normality is significant for the residuals. Is this because the range is too small to be converted to any type of...