# Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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### Why doesn't adding additional explanatory variables in a logistic regression model decrease our primary explanatory variables variance?

Imagine a clinical trial setting where we have binary outcome Y and we are interested in the effects of treatment X. Lets say we also have additional explanatory covariates Z and W. Thus our ...
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### MLE to address multicollinearity in linear regression

OLS estimation assumes that the explanatory variables are independent in the linear regression model. There isn't such assumption when using the MLE estimation. So, my question is, can we use MLE to ...
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### OLS R-Squared from Sliced OLS Regression

I have the following question: suppose we have a data set with 3000 observations $(X,y)$ and $X$ can be matrix. So we want to use a bunch of features to predict $y$. Suppose we sliced the data into ...
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1 vote
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### How to test whether there is a significant (general) within group trend with data from many groups

I am having trouble identifying the correct statistical method for the following problem: I have data on a characteristic (e.g. body length) from several individuals per species, distributed in an ...
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1 vote
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### How to interpret the coefficient of a limited independent Variable (Index)?

I assume this is a very simple question, however I am not sure about it. I have a regression table in front of me that contains the coefficients of a linear regression. The dependent variable is ...
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### How to optimize a clinical scoring algorithm?

I've made two studies on clinical data that correlates with a disease. The clinical data can be aggregated into a score, such that the higher the score the higher your % of having the disease. However,...
• 1,861
1 vote
19 views

### Combining/updating parameters from multiple estimations

Take a simple example of performing two independent linear regressions on a set of x-y data, in the form of y = mx + b, each using half of the data. I will obtain two separate estimates for m1, b1, m2,...
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### How do I interpret a regression model when there are impossible additive effects?

Let's say I have a model of count data as a function of the month of the year along with an additive effect of season (factor with 2 levels Wet and Dry which correspond to Jan - June and July to Dec ...
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1 vote
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### What is the difference between lm() function and caret::train() function when it comes to creating linear regression models? [duplicate]

When applying the lm function as follows (the assumptions were not considered. The purpose of this example is just to make my question clear) : ...
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### Entropy Balancing and regression

I have a panel data set consisting of a treatment and a control group. The control group contains much more observations than the treatment group. In order to adjust some specific Variables between ...
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### What is the inverse normal transformation (INT) and what are the reasons behind using it?

I noticed a statistical method called inverse normal transformation in the following research article FTO genotype is associated with phenotypic variability of body mass index. I attached the ...
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1 vote
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### Panel data regression with time varying treatments and fixed effects

Experts, I have some trouble concerning my regression model for a panel data analysis. The dataset includes observations of 200 firms over a period of 6 years (2000 - 2005) regarding merger activities ...
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1 vote
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### Question on estimating (OLS) the ATE of RCT with multiple (2) treatments

Updated: I do not have enough points to comment so... Thank you Ben, you did interpret my question correctly. There are three treatment categories: control, A, and B. Thank you for clarifying that ...
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### How does one deal with linear regression with heteroscedasticity?

Suppose I have a dataset with outcome continuous. I applied various transformations on either covariate, outcome or both. I have also tried polynomial terms. I always get over heteroscedasticity when ...
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1 vote
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### Marginal structural model - help with some concepts

I'm trying to gain some (deeper) understanding of MSM's - what exactly they are and when they might be appropriate to use. Are my thoughts on the following correct (please feel free to correct any ...
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### How do we make predictions for future data when you have lagged dependent features used in training?

I am executing a lightGBM model to forecast my units sold (qty) over a period of time. Objective is to run a model for each product group and be able to capture the trends, price elasticity, etc and ...
34 views

### Anova with stratified Cox model

I'd like to use anova to investigate which variables are important to my Cox model outcome. I tried using anova from ...
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### How to represent the interval or uncertainty on regression predictions in an 'experimental vs predicted' plot?

Using an example similar to the one from R predict, simulate some independent variable ($x$) data, map them to an observed ...
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1 vote
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### Ordinal regression or Spearman rho

I am a complete beginner in statistics and I am confuse which method is more appropriate. I have two variables; The independent variable is continuous ( hours) while my dependent variable is ordinal ...
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