regression

  1. R

    partial regression/residual plot

    Dear all, We have run a multiple regression analysis in SPSS in which we examined the link between telomere length and anxiety symptoms, while adjusting for the effects of age, IQ, socioeconomic status, and BMI. We would like to present our results graphically using a scatterplot with...
  2. M

    Regression with additive and multiplicative predictors

    Hi, we are analyzing pollutants [µg/kg] in mussels with regression models. Let's say we have only the two predictors (1) "year" and (2) "month". However, the effect of "year" on the outcome is assumed to be additive, i.e., in avergage a constant amount of poullutants is added each year...
  3. L

    Logistic Regression of Weekly NFL Data

    This guy uses a type of regression to predict NFL games: http://trevorbischoff.com/amos-2016-nfl-predictor/
  4. A

    Multiple Linear Regression (Actual Vs Predicted)

    Hi forum, I am new to statistics and R in general so please bear with me if I am not clear enough. So I am generating a 3 level full factorial design with 4 variables (P, P1, P4, INJ), and three responses (qo, qw, qg) which I am using in order to run a multiple linear regression on in R. I have...
  5. S

    Regression Analysis thoughts - Could I model my data this particular way?

    Hello, Looking for a guidng hand with a regression problem that I have managed to create. Apologies for my lack of statistical knowledge, but if you need any more information in order to give advice please let me know. I have run an experiment with one group of participants (n=20). Each...
  6. M

    Regression with data from different sources: Nested fixed effects possible?

    Assume I have collected my data with 3 different methods, each method share the same outcome Y as well as the predictor X. I am interested in the dependency of Y on X via regression analysis. However, each method has additionally a unique set of fixed or random effects (A,B,...), which are...
  7. S

    Regression analysis with sales forecasting

    Hello, I am in the process of using a regression model to help predict the forecast of soft drinks. I have 52 sets of weekly data and my independent variables are feature space, temperature, price, competitor price and competitor feature space after having omitted some predictor variables due...
  8. G

    Multi-level modeling?

    I've spent the last two days reading and attempting to find an answer to my question but I am unsure if the answers that I am finding are even accurate because to be honest, I am not sure what to call the analysis that I am attempting to use. I am using SPSS for analysis procedures, so any help...
  9. S

    Regression and seasonality

    I am running a multiple linear regression analysis to show how different demand factors affect demand of juice. My independent variables are price, temperature, competitor price, feature space and competitor feature space. However, I know there is an element of seasonality which is affecting the...
  10. L

    R - bootstrap confidence intervals, Create a matrix, Perform stepwise regressions

    I'm brand to statistics and taking my 1st class in almost 40 years, so I'm quite a bit behind the times. On top of all of that, I am not very computer savvy, and have very little experience using any technical functions with computers, outside of checking email. I have no programming experience...
  11. L

    Need Help with developing general linear mixed model regression equation

    general linear mixed model regression equation I'll be moving this to another thread and don't want to create multiple versions. Thanks!
  12. T

    Determining residual outliers when heteroskedasticity exists

    Hi, I was wondering if anyone has any thoughts on the best way to approach the detection of outliers based on residuals from a linear regression when heteroskedasticity exists. For example, if the variance in the upper end of the the dependent variable increases with an increase in an...
  13. K

    Binary logistic regression

    Hi there i ran logistic regression and got the following model: var1: B = -5.670 Sig = 0.01 Exp (B) 0.003 Constant: B = -0.469 Since the B is negative, is it true to say that for every one unit increase in var1 there is a 99.7 (1-odds ratio) chance of a decrease in the outcome (in...
  14. G

    Regression on two explicative variables

    Hello, I am currently doing a thesis which aims to explain returns of stocks in function of the ownerships of some stakeholders. In the Excel attached, I would like to explain the returns in the last column with the two explicative variables ( Venture Capital % Ownership and Hedge Funds %...
  15. P

    Hypothesis for logistic regression

    I get a group of data and would like to use the regression to analysis the relationship. The dependent variable Y is a kind of loss rate, so it is strictly belong to [0, 1], e.g. I have $100, and I will loss 5% at day 1, 3% on day 2, 4% day 3, ...then Y is (5%, 3%, 4%, ....); I also have some...
  16. C

    Cox's regression

    Hello, I have some experimental data for animals with tumours. Unfortunately, they were not followed individually during a time course, but evaluated as groups. As a result, I have 6 predictors only for animals that have survived for each time point. I would like to test which of these...
  17. S

    2 or 3 level multilevel model? Quick query

    Hi there, The title should read 3 or 4 level multilevel model, my apologies. I am estimating a multilevel model (in Stata). My goal is to examine the effects of the explanatory variables on the country level. My data is clustered within age cohorts and then countries with years clustered...
  18. E

    please help : modelization

    Hello, I have a distribution which looks like a Khi-2 distribution, which model is most appropriate? I try linear regression, but normal distribution is not suitable. Thanks for your help ! :)
  19. J

    Testing Simple Effects for Generalized Linear Regression

    Hello, I have found significant interaction effects when analyzing a negative binomial generalized linear regression model. However, I am not sure how to further explore the interaction. I am currently using SPSS. How can I conduct follow-up simple effects to examine the interactions? Can I...
  20. D

    Data set simulation

    Answered on other threads, sorry for posting