regression analysis

  1. M

    ANOVA after logistic regression?

    I have fire incidences data with variables - seasons (summer & winter), time taken by fire truck to arrive (Early (<30 mins) and Late (>30 mins)), area (area code), small fire incident (1=Yes, 0=No), and big fire incident (1=Yes, 0=No). It has multiple observations recorded from multiple...
  2. L

    Hierarchical regression building support

    Hello all, I am building some regression models to look at the contribution effect of stigma on various pain outcomes. I have a large sample size (N=974). I've done my normality and collinearity testing as recommended. I have two demographic factors to include in block 1 (age and duration of...
  3. H

    Math behind Pareto chart of standardized effects

    I would like to understand the math behind the graph that Minitab computes explained here, which I have encountered a couple of times in publications regarding regression modeling such as example1, example2. According to the Minitab website, the bars represent each term in the regression...
  4. R

    Regression without time variable

    Hi, I have a large dataset from a register based study. We are using Stata 17. We have demographics, dates for hospitalisations and diagnosis codes from hospital visits in a given period. We want to do a regression on potential risk factors for myocardial infarctions, however, we only have the...
  5. N

    Finance: Price to Earnings Multiple for the FTSE 100 and its drivers.

    Hi All - I have built a very simple model. I have developed a regression model in MS EXCEL to predict if the FTSE 100 is fairly, under, or overvalued. Forecasting EPS: Dependent variable - Trailing 12 months EPS (£) Independent Variables - Brent Crude Price ($), Bloomberg Industrials Metal...
  6. V

    Right-skewed DV with heteroskedasticity

    Dear all, I'm looking to fit a linear model for my rather large sample (N=~400) where the dependent variable distribution is right-skewed (satisfaction scores, which have that tendency) and the assumption of homoskedasticity is violated. Now, I do know that log-transforming the DV can help...
  7. A

    Regression modeling

    Hello everyone, I am a student in agricultural genetic engineering, and I am working on presenting a research paper about the genetic relationship between efficiency of feed intake and diseases. This paper presents a lot of statistical information which is quite hard for me to process quickly...
  8. N

    Unbiasedness of the Variance of the Error Term in an intercept-only Model

    Hi folks, Is there anyone that might help me with the following derivation to show that the estimated variance error term is unbiased? I have managed to do the first and the second step, however I am currently stuck at the third step since I don't know how to replace Yi by µ^. The model itself...
  9. M

    What Test Should I Use?

    Hi there, I am analysing a large data set involving a food-training study, and I am struggling with the last question. Here are the key facts: The participants were 83 people aged 18–65 with a body mass index (BMI) of at least 18.5. All participants were weighed at baseline (Week 1, prior to...
  10. M

    Is it possible to run a multiple linear regression analysis when one of the categorical predictors has more than 2 groups?

    I want to run a multiple linear regression analysis with 5 categorical or continuous predictors (independent variables) for a continuous outcome (dependent variable). Is it possible to use a multiple linear regression analysis if one of the predictors has more than 2 groups?
  11. A

    Tobit Regression

    Can I use categorical independent variables in tobit regression? If yes, how to interpret the results?
  12. W

    R^2 vs. significance of the the variables

    Hello community :) I am currently working with paneldata to see if there is correlation between sustainability and performancce in the energy and materials sector of the S&P500. I ran the regression twice, one with the logarithm of MarketValue (=MarketValue.WINS.LOG) and one without...
  13. K

    Difference between simulating the dependent variable and simulating the error terms and adding them to the fitted values values assuming normality?

    What's the statistical difference between simulating the dependent variable and simulating the error terms and adding them to the fitted values values assuming normality (gaussian GLM)? Say I'm doing a simple multiple regression on the following data (R): n <- 40 x1 <- rnorm(n, mean=3, sd=1)...
  14. S

    Adjusted OR

    How to find adjusted OR as given in Table 6 in spss? The procedure followed to get it like i found binary logistic regression is used to find crude OR using single indep. variable.
  15. Y

    Multiple or simple linear regression?

    Hi all I'm fairly new to statistics and have a project where I investigate if the difference between two variables can predict the value of a third variable. And I am unsure if I should use simple or multiple regression. The participants in my sample has answered three surveys: A) Emotions...
  16. R

    Urgent Help for Statistic

    I have a study to establish the factors that influence consumer satisfaction with different internet banking services. Part 1 is the demographic and Part 2 are the Customer Satisfaction and Attributes of Satisfaction which were measured using the 5 Point Likert Scale questionnaires. The...
  17. R

    SPSS for Customer Satisfaction

    I have data collected with 5 Likert Scale Questionnaire to establish factors influencing customer satisfaction using online banking. The factors included Credibility, Efficiency, Ease of Use, Security, Problem Handling and Product/Service Portfolio. A total of 6 independent variables. In this...
  18. C

    Need help choosing the right analysis [unsolved]

    Hi! I am using three surveys, let's call them A, B, and C. From one survey to the next, there is a 5-year interval. From these surveys, I calculate the weight change and I then check if they get a certain diagnosis afterward within 10 years. I want to see if weight increase or decrease is...
  19. StrangeCharm

    Which approach to evaluate small spatial variations in temperature?

    I am evaluating whether utility-scale solar energy plants affect the surrounding climate (initially temperature). An effect has been found in one paper using the approach described below/attached but when repeating this approach I find no effect for the same site. I want to be sure that there...
  20. C

    Standardize one predictor variable or all predictor variables to solve multi-collinearity

    I was using a fixed-effects panel model with interaction effects when I realized that the VIF values are too high for some variables. I was advised to standardize the predictor variables to mitigate multi-collinearity. My question is that can I standardize just 1 predictor variable or must I...