# regression

1. ### Multicategorical logistic regression in LPA/LCA analysis?

Hi all, I am doing an LPA analysis, and I would like to know when I have completed the category classification for the subsequent Multicategorical logistic analysis. What does a reference group I better set? I have seen some papers that set a baseline group, after which all other groups are...
2. ### Polynomial regression Coefficient SE results are different from examples

Hi, I am running a polynomial regression on 5 sample dilutions and when I am calculating it on my software the results are different. The raw data is For example my results for the cubic is as follows: However, in the example given the standard error of the coefficients are different as...
3. ### Comparing outcomes of two treatment groups: t-test/Mann-Whitney U versus regression

Hi all - I'm a student and had a question about statistical analysis. I'd like to compare post-treatment outcomes between two groups: group A who received a traditional drug (n = 200), and group B who received a newer drug (n = 100). Some post-treatment outcomes are continuous, whereas others...
4. ### Need Help Finding Whats Stats To Perform

Hi there, I've been given a data set involving a food-training study. In week 1, baseline weight and BMI were recorded for each participant. In week 2, participants underwent four sessions of an online go/no-go response inhibition task. The task involved two treatments: food inhibition and...
5. ### R-squared is too high

I just want to ask on how to make the R-square decrease without ruining the model. My research is about economics and the R-squared is said to be too high.
6. ### Which analysis is adequate: ANCOVA, multilevel...?

In the experiment, after a baseline assessment, participants will be assigned to one of two conditions (between-subjects factor). In condition A, I expect their response time to be higher in large stimuli than in small stimuli, but slower in colored stimuli than in b/w stimuli compared to their...
7. ### Why is an interaction term better than two regressions?

I have struggled with the "because it is" and vague answers on this topic for a while and I was hoping someone could actually give a real reason why using an interaction term in regression is better than doing two regressions. For example: While doing a GLM to see how environmental factors...
8. ### Help with creating a model!?

I want to create a model that assesses the effect of Drone usage (binary) in transporting medical samples to laboratories on Treatment Success (also binary). I was thinking: Dependent: TS = treatment success, so either successful or unsuccessful. Independent: TAT = turnaround time = the...
9. ### Help determining start values of coefficients for a nonlinear model

Hi everyone. For a dataset consisting of three quantitative variables, H, M and W I have to build a non linear model of this form: E(H)=b0+b1*M+(W/(b3+b4*M)). I tried using the "nls()" function in R, but I don't know how to determine the start values of the coefficients, b0, b1, b3 and b4. Can...
10. ### Spurious Regression with non stationary time-series

Hi everyone, I'd like to have a confirmation on the correctness of the following interpretation: Let say that we want to run a very simple regression like the following one: We are regressing two I(1) series since x and y are assumed to be both described by a random walk process. The errors of...
11. ### Doubt on a model

Hi everyone, for an universitary assignment, I have to model one dependent variable H based on two other independent variables, M and W; the model I have to fit to the data is this: E(H)=b0+b1*M+(W/(b3+b4*M)) do you have any clue on what kind of model this is and how can it be adapted in R?
12. ### Multiple Regression

I have been given a college assignment and need to interpret these results (see attached). From what I can understand, the Annual Personal Outcome is the DV and there are several IVs (i.e gender, sexual orientation etc.). As such, has a multiple linear regression been conducted here? I'm...
13. ### 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. ### Treatment of Coefficients from Regression Using Lagged Independent Variables

I'm running a regression on two time series of financial returns, one dependent and one explanatory/independent. For the explanatory time series, I'm creating several lagged versions and using all of them as independent variables in in a multiple linear regression. My question is, how do I...
15. ### What statistical test should I use?

Hi there, I'm currently in the process of carrying out a systematic review and I've gathered cost estimates from studies for a specific type of treatment (with two different approaches), I am interested in finding out if these costs have decreased over time. I have 40 cost estimates for the...
16. ### Ordinal Logistic Regression

Hello! I am trying to perform an ordinal logistic regression (or at least I think I am) and I'm a bit stuck. My variables are all categorical or ordinal: DV: High, Medium, Low IV: Parent Gender: 0,1 Child Gender: 0,1 Essentially, I am trying to understand if a parent's gender...
17. ### How to Improve my Hosmer-Lemeshow Goodness of Fit Significance Value

Hi, I'm just wondering if anyone here can help me. I'm making a model for my logistic regression. For the variables, I'm using 1 Dichotomous Dependent Variable (Financial Distresss, Y) and 2 Continuous Independent Variable (Corporate Governance Score, X and VAIC Score, Z). I'm using logistic...
18. ### Two dummy variables are mutually exclusive

Hello all, I have a problem for a university assignment that two dummy variables are mutually exclusive. The task is to estimate what can increase certain diseases in dogs using regression. In the sample there are several factors (Lives in city yes/no, age, male/female etc....). Then there is a...
19. ### How is conditional main effect interpreted when there is interaction?

I have a question about multiple regression. May I kindly ask how should I interpret the conditional main effect when the interaction is 0 and the coefficients have opposite signs, more specifically if one of the interaction term contains zero such as angle or time. Please see an example...
20. ### SPSS - Using mixed univariate ANOVA (UNIANOVA) or mixed linear regression (MIXED) instead of repeated-measures ANOVA

Which process is better for using instead of Repeated-Measures ANOVA (SPSS syntax: GLM -- GUI command: Analyze --> General Linear Model --> Repeated Measures)? and Why? (1) Mixed univariate ANOVA (SPSS syntax: "UNIANOVA" -- GUI command: Analyze --> General Linear Model --> Univariate) (2)...