regresion analysis

  1. E

    Multiple regression - Two independent variables

    Hi, I was given the following task in a course: You examine the influence of the two variables QS and TR on the variable WF. You have estimated the following relationship: WF= - QS - TR + 4QS • TR + ε WF is your dependent variable. The variables QS and TR are your independent variables. ε is...
  2. F

    No change in the coefficients of my time-specific variables of interest when controlling for demographic effects

    Ciao Guys, I have a balanced panel set and I study the following model: lm(value ~ taskXjan20 + taskXfeb20 + taskXmar20 + taskXapr20 + demographic_criteria), where value is a binary variable, being 1 if individual i has been unemployed in the previous month and 0 otherwise. It expresses...
  3. G

    Analysing 2-factor 2-level design as if it were 4 different treatment design

    Hello! Just curious why we see different results in such cases. Here we have a classic 2-factor 2-level factorial design which we can analyze using Nominal regression/logistic regression. Analysis shows that only interaction is significant : However, if we transform this data as if there...
  4. T

    Correct model for outcome variable with 4 categories

    I am working on a study that measures the association between BMI(exposure) and multi level(outcome). I am testing with BMI both continuously and categorically, but the outcome is a score with 4 levels. I am having trouble deciding on correct regression analysis for an outcome of 4 levels. If...
  5. D

    Willingness to pay premium influenced by internal factors and preferences for external factors

    Hello Talk Stats Community, I'm a new member and very happy to be able to open a thread :) I'm a grad student and currently working on my Expose for the Masterthesis. I want to contribute to the literature of sustainable living and green apparel with empirical research on willingness to pay a...
  6. K

    Interpretating hierarchical regression results

    Hello, I’m needing a little bit of direction in understand my first hierarchical multiple regression data. My research question is to what extent does alcohol explain the association between negative mood and impulsivity in academic performance (DV). I’ve ran the analysis - at the first stage...
  7. D

    vibration signal_prediction

    Hello, I have a vibration data coming from a motor. i am using R program to do the predictive analysis. My vibration data is a white noise (mean and variance are constant). I need to use this vibration data to do the prediction. How do i use this signal for prediction? Do i need to do some...
  8. S

    Interpreting VECM/ ECM result

    Hi, I am currently working on a paper where I run a VECM and get significant values. However, I am not quite sure about how to interpret the output and how take the different values and express them with an equation. I run the test in SATA using the vec command Attached is a picture of...
  9. L

    F (18, 95) = 6.009, p < 0.0005

    I was looking into a research paper, and this F value was provided when using a regression model. I do not understand, what is the need to discuss F value in a paper? It is just an intermediary value. Or, does it really help in understanding some fact other than observed from...
  10. P

    Can I draw an interaction plot using Generalised Estimating Equations (GEE)?

    Hello, Can I draw an interaction plot using Generalised Estimating Equations (GEE)? If yes, how? Thanks.
  11. M

    Testing the Normality of Errors in Regression?

    Hi all, I have simple conceptual question: In the simple linear regression problem, where the true relationship is, y = ax + b + e the error terms, e , are assumed to be normally distributed N(0,\sigma^2) . However, linear regression only yields estimates \alpha \approx a and \beta...
  12. T

    Beta NO Intercept purpose

    Hey guys, What would a Beta with NO intercept tell me about a time series model?
  13. A

    panel regression vs cross-section

    Hi, I'm running the following regression: y=A+Bx+...+year_dummy for the years 2002-2005 and get that B is statistically significant. However, when I run separate regressions for each year, the significance disappears (for all years). I'm having a hard time interpreting the results - any...
  14. A

    Crises: ANOVA? How to analyse non-normal, non-Homogeneity data with different N group

    Dear all, I'm somewhat new the world of statistics, or at least it has been years since I last used it and basically the only program I know generally how to work with is SPSS. However, for my Master thesis I need to analyse a dataset I made, so there's no escaping it now. My research is...
  15. B

    Confusions regarding Regression, Multicollinearity and Factor Analysis

    I am currently working with a data set that contains about 26 IVs of almost all sorts of scale of measurement (binary, nominal, ordinal and interval scale variables). There are strong reasons to suspect that some variables are probably highly correlated, while some may not be related to any...
  16. M

    How to do Regression with many replicates of y at each level of x?

    Hi follows, I have data that looks as follows: X, y1, y2, y3, y4 0, 54.241, 127.728, 127.73802, 127.73802 31, 65.132, 127.729, 127.73787, 127.73792 59, 65.364, 127.729, 127.73782, 127.73789 Where y1-y4 are just independent...
  17. D

    Binary logistic regression. missing values

    Hi. I have a question about missing values. My dependent value is whether the respondend voted in the last election or not - N=2600 cases. I want to build a model with several independent variables (income, education, parrty identification etc.) but I have a problem. If these independent...
  18. V

    How to use a regression analyis to cross calibrate two sensors

    I have two temperature sensors that I need to calibrate to each other, and I'm thinking a regression analysis is the best way to go about this. But I'm hoping to get some advice on the best way to do this. My problem has two steps: Step 1- I place both temperature sensors in the same...
  19. B

    Confused with SEM and factor analysis

    Hello, I am confused about what to do with the data set This data set has 29 variables, of which we have to discard the variables ID, FTEequivalent and Size as they are unnecessary. From the remaining ones, we have four dependent...