regression analysis

  1. R

    Help deciding which spss functions to use

    I'll start off saying that stats in general has never been a strong point for me :D The variables i am using are; Gender Age Relationship Status Number of dependants Profession Neuroticism (Higher score = higher neuroticism) Affectivity (Higher score = positive; lower...
  2. A

    De-trending before regression analysis

    I'm currently analysing two sets of time series data (monthly temperature and forest cover over a 10 year period). I first ran a Mann Kendall on each variable (they're non-normal) after removing seasonality, and found that they both show a significant increasing trend - vegetation faster than...
  3. E

    Multiple Linear Regression Assumptions

    Hi guys! I am gonna model multiple linear regression. Do you think that normality of residuals assumption is met according to the P-P plot? Also, consider the homoscadasticity assumption according to the scatter please. I am writing my Bsc. thesis, what should I do if these two assumptions...
  4. L

    Sufficient linearity between predictor and response variables?

    Hello everyone, for a multiple regression I am currently trying to understand if there is sufficient linearity between my predictor and response variables to see whether I can carry on with a regular linear regression. I have three models, with one dependent and the same three...
  5. B

    FE, RE, OLS Cluster?

    Hi all, I've a question which regression model to use? I've the following model: Taxavoid= PC + Before/after + PC * Befor/after tax avoid = continious where PC is ratio variable of political party/ i coudl have used 1 or 0 (REPvsDEM) but, I use ratio, more info. PC= REP / (DEM+REP) so ratio...
  6. L

    Can an odd ratio be as low as <0.001?

    With a 95% CI of <0.001 to >999.999? Any idea what could be wrong? (Sorry about the french output, will gladly provide more info if needed) Thanks a lot!
  7. N

    Best method to determine future success or to determine best linearity?

    Long time viewer, but first time poster, so excuse me if i'm in the wrong place please. Anyway, I am working on a project that is pretty interesting. Through data mining, I am able to gather a ton of investment portfolios. Each portfolio has the obviously related statistics, including total...
  8. V

    Can I remove these outliers?

    Hi, is it acceptable if I remove the outliers with charges above 55k for this regression analysis? Or is there any other option to minimize their impact in the model? Thank you
  9. N

    What Model or Calculator should I use to set the right target?

    I have a production target in which 90% of widgets must be completed within 2 hours. The production process has two main components. Process A + Process B (together these have to be completed within 2 hours, 90% of the time). (quick note: Process A is the simpler process) I want to establish...
  10. A

    Multiple Imputation in SPSS: What to do and report

    Hi everyone :) I'm currently working on a research question where there are 2 categorical predictor variables (one with 2 levels between subjects, the other with 7 levels within subjects) and one continuous response variable. I want to conduct a simple repeated measures ANOVA in SPSS. The...
  11. A

    Do I need to rescale variables to compare coefficients.

    I'm running a regression analysis. My "Y" variable is Yearly_Spend while my "X" variables are Time_Spent (on website in minutes) and Length (of membership in years). Right now my results show Years has a bigger impact on Yearly_Spend. Do get a true apples to apples comparison of the...
  12. A

    Different coefficients from regression and trendline equation

    I have two variables 'x' and 'y'. I took the natural log of the 'y' variable and then plotted the ln(y) vs x on a scatterplot in excel. I added a logarithmic trendline which seems to fit perfectly. The line equation is y = 1.1282*ln(x) + 12.183 with an R-Squared of 89%. However when I run the...
  13. D

    Logistic regression or something else?

    I have a dependent binary outcome and 6 independent variables. These are measured in the same group of people at two moments in time in a descriptive longitudinal study. I am assessing whether these independent variables increase the likelihood of achieving the binary outcome. I know that I...
  14. S

    regression coefficient as average effect

    In OLS, given the regression equation y = B0 + B1X, why do I often read that B1 represents the average effect of a predictor? I don't get that. For example, data <- data.frame(sex=c("male","female","male","female","male","female","male","female"), DV=c(22,32,34,16,66,34,77,23)) The average...
  15. J

    multivariable regression equation with interaction terms for difference-in-difference method

    I am doing a difference-in-difference analysis on a set of survey data for a health education program and I need to find statistical significance for the difference-in-difference estimate. I know that I find this using a regression. I need to use a regression in a mixed logistic model including...
  16. J

    Why does the “linear regression t-test” return a p-value (two-tailed) from regression that is twice the p-value from ANOVA? (Binary predictor)

    I'm using the "linear regression t-test" guide at The guide shows calculating t =b1/SE, where b1 and SE are provided by the regression function (here lm() - using R.) The guide shows the p-value gets doubled as this is a two-sided test...
  17. P

    How to interpret log differences in a partial log-log regression

    I'm currently trying to understand the relationship between firm performance and various independent variables (e.g. firm size, firm profits..). Now, the regression I'm estimating looks like the following: Δlog(firm_performance) = α + β1 Δlog(firm_size) + β2(other_variable) + ε Where Δ...
  18. T

    Regression coefficient interpretation

    Hi, i have run a regression to estimate the impact of couple of variables like growth rate, company size or leverage on the profitability of a firm. I know that if e.g. the regression coefficient for growth is 0,5 a 1% increase in growth rate would yield a 0,5% increase in profitability if...
  19. T

    Why are so many variables in my regression significant?

    Dear everone, For my research I am trying to define the impact of certain elements on a company's goodwill impairment. For my regression analysis I deflated the following variables by the lag total assets: - gdwlia (dependent variable) - ROA - BM - difference in turnover between year t-1...
  20. R

    Multiple Linear Regression: to split or not the data

    Hi all, I'm currently modelling running performance using multiple linear regression. The data has GENDER and AGE as inputs amongst others, the target is RACE_TIME. I've partitioned the data into training and test for cross validation purposes. I've tried a couple of approaches 1) to generate...