Questions tagged [controlling-for-a-variable]

A control variable is one which is included in a model primarily for its impact on the total model rather than for its own substantive interest.

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Focal Predictions from a linear model: How to test for difference between factor levels (pairwise) instead of comparing errorbars?

Sorry for the cluelessness, I know this is a topic that arises often in different variations. Still, I couldn't find an answer for my situation. In my work, I sample people and try to generalize the ...
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Generate null distribution from pvalues

I have a set of experiments on which I apply the Fisher's exact test to statistically infer changes in cellular populations. Some of the data are dummy experiments that model our control experiments ...
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Controlling for confounding variables with multiple regression - isn't correlation a problem?

From the Wikipedia definition - "a confounder (also confounding variable, confounding factor, or lurking variable) is a variable that influences both the dependent variable and independent ...
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Failing to fully control for a variable

Lets assume we want to perform a 'reduced-form' causal analysis to evaluate the impact of a program on the dependent variable of interest. (However the question is more universal). Lets further assume,...
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Multiple regression: Is it acceptable to include a categorical covariate with few observations across levels?

I am interested in the influence of age and body mass index (bmi) on brain size in a patient group. I have the following multiple regression model (using R): ...
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Omitted Variable Bias (OVB) and multicollinearity

In a linear regression model, the reason we control for variables is to prevent the omitted variable bias (OVB). That is, suppose we are trying to fit the model $$ Y = \beta_{0} + \beta_{1}X_{1} + \...
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Forcing control variables into an Adaptive LASSO model?

I am using code modified from here to perform an Adaptive LASSO analysis. My question is: if I wanted to "force" some control variables into the model. Is there a way to do this? Using the ...
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How do I designate a variable in a linear model to be a covariate in R?

So I want to make this equation for example: y = mu + Strain + Insect + Strain*Insect + BW_final Of all these variables, strain and Insect are controlled variables, but BW_final is an independent ...
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Zero-inflated poisson/nb — which covariates should I put in the inflation (logit) model and which should I put in the count model?

I'm using a zero inflated count model (either poisson or negative binomial). I have a set of control variables that I want to include in addition to the main independent variable of interest. Can ...
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Interpreting effect sizes with additional covariates in the model

I have a question about interpreting effect sizes. Let's say I have one model in which the main independent variable is statistically significant with an effect size of .25. I add additional ...
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Can I control for a variable, post-hoc, using rejection sampling (and bootstrapping)?

Context, Goal: To estimate the quantitative effect of the treatment on a continuous dependent variable, while controlling for another continuous variable. I have one sample each from a test (n=918) ...
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Do I need to control for prognostic variables in a Cox PH model that estimates a treatment effect if the sample matches the target population?

I've been told that if all known prognostic factors are not adjusted for in a non linear model, in this case a Cox PH model, that because the error term is not estimated the treatment variable will ...
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Controlled Intervention Before/After

I have an intervention that I'd like to determine the effect of (before/after). All of the data has been divided into a treatment or control group. The issue is that the treatment/intervention took ...
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Should I include country dummies when I combine datasets of 3 countries?

I am currently doing the analysis using firm-level data of three countries combining together. Also, it is a cross-sectional analysis. Therefore, in the Ordered Probit regression, I control for ...
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What does 'control' in controlled experiment refer to?

Does 'control' in controlled experiment refer to: Having a control group for comparison, i.e "an experiment or trial that uses controls, usually separating the subjects into one or more control ...
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What is the difference between “including fixed effect” and “including control variables”?

In this paper Heider, Florian, and Alexander Ljungqvist. "As certain as debt and taxes: Estimating the tax sensitivity of leverage from state tax changes." Journal of financial economics 118.3 (2015):...
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Interpretation of VAR results with exogenous variables

I have three time series A, B and C and I ran a VAR using C as a exogenous variable. I add that the B variable is likely associated with C, in the sense that B could have a casual impact on C. I ...
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Can controlling for baseline in a regression with change scores be appropriate? (within-subjects design)

I ran a regression model with a change score (post minus pre manipulation) predicting my dependent variable. Initially, I thought it might be also interesting to control for the baseline score (pre ...
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Manipulating neuropsychology test items, controlling for changes?

If I take a subtest from an existing neuropsychological test, and take out 5 items to use independently as my methods of measurement for each level of my within-subjects factor, how can I ensure good ...
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How does an unbalanced nuisance factor influence my outcomes

I am retrospectively analyzing a specialized dataset of low sample size with only four subjects. All of the subjects' dependent variables were recorded in three conditions (levels: A, B, C) within ...
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Do control variables need to be added for the following parallel trends assumption test for diff-in-diff?

I completed the following test for parallel trends Difference in Difference method: how to test for assumption of common trend between treatment and control group? However, I am unsure as to whether ...
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What to do when difference-in-differences affects covariates

Consider the model $y_{it} = \alpha_i + \beta_{it}did_{it} + \gamma_{it} + \phi_i + \zeta_t + \varepsilon_{it}$ for group $i$ and year $t$. $\phi_i$ refers to group fixed effects and $\zeta_t$ to ...
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Predicting house prices with machine learning. Problem with time-varying variables

I'm currently trying to cross-sectionally predict house prices using statistical learning methods. I have collected prices from 2009 until 2020. I have loads of time-invariant variables on the ...
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If I control for country effects and results are significant, can I conclude generalizability of results?

I am working on a mediated model where M mediates the relationship between X and Y and I have one control variable. The data I am using is from 3 different countries with different sample sizes (46, ...
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How to control for difference a group difference in pre-test in repeated measures MANOVA

I'm evaluating the effectiveness of an intervention. My primary outcomes include aggression and institutional infractions. I ran a repeated measures MANOVA with group condition (intervention versus ...
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Am I correctly controlling for variables in multiple regression?

I want to run a OLS regression that predicts total violent crime per year using annual violent video game sales as a predictor variable. I also want to control for age, sex and race. I have data on ...
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Excluding the effect of control variables in the assessment of a logistic regression model

I have a logistic regression model with ten independent variables of which two are included as controls. While their inclusion is necessary for correctly assessing the coefficients of the other ...
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Blocking vs. Control

Am I thinking about this correctly? Blocking is something that is done on the experimental design level: If I'm not interested in the differences between school districts, I block by school district ...
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control variable, industry

I'm doing a master thesis on the effect of CSR contracting on CSR performance. My model is based on a multiples regression by OLS. I have regressed CSR level on CSR contracting and used several ...
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How to check for relevant covariates in difference-in-difference regression?

I am conducting a diff-in-diff regression over two periods of time with the treatment in between. Next to the dummy variable time ('Post'), I have 3 groups for the other variable and therefore 2 dummy ...
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Pre-Post Analysis and Accounting for Task Difficulty

The study We have a real world pre-post design where some people were trained and others were not trained. The goal is to determine if the training worked and improved performance overall. The ...
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Controlling variables for interaction effects

I'm trying to understand what adding a 3rd covariate to a regression model does to the overall effects on interaction effects. I'll be using the mtcars dataset in R ...
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Help with Interpreting results from 2 models: Variance explained vs Indirect Effects?

I am comparing two models using Path Analysis (pictured). Model A explained 49% of the variance in my DV. Model B (which is the same as Model A + an additional mediator) explained 48% of the variance ...
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How to control for demographic variables in Path Analysis?

I am running a series of path analyses using AMOS and could desperately use some help around how to control for confounding demographic variables; Q1. I have read that while some demographic ...
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Capturing effects / Controlling for variables [duplicate]

I understand the idea behind regressions and know how to interpret them, however, when I hear the term "capturing the effect of.." or "controlling for.." so far I've just accepted it without ...
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How to control for a numeric variable when doing a chi square goodness of fit test? [closed]

I'm looking at race differences in the number of adverse events that happen at a hospital. At this hospital there are a lot more white people in general so I've been using a chi square goodness of fit ...
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Is it ok to use control variables in a moderator/interaction analysis in experimental design?

I have a question concerning the inclusion of control variables into my research. I have data from an experimental, randomly distributed social protection program. I want to test whether a moderating ...
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Controlling for a variable: t-test or covariate?

Lets say I have some data that looks like this: ...
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Using regression to solve an expenditure minimization problem

I'm working with some data and I want to choose capital and labour expenditures in order to minimize total expenditures subject to the constraint that they produce a certain level of output. The issue ...
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Controlling for variables in social sciences

I know this is a completely hypothetical scenario but I just want to understand how the effect of a variable could be held constant and how the coefficients of two independent variables are estimated ...
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Do control variables in a regression analysis cause collinearity?

This is something that bothers me for quite some time, but I didn't find yet a satisfactory answer. I hope that the wisdom of the people hear will help me to clarify this: In a multivariate ...
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How to choose the control variables in the conditional expectation to hold fixed when studying a causal relationship

I'm reading the introductory chapter of the wooldridge's book, "Econometric analysis of cross section and panel data". The chapter begins by highlighting the role and importance of conditional ...
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controlling confounding variables vs. excluding confounding variables

I'm working on a meta-analysis project that looks at the effect of "pure" depression (i.e., depression with no anxiety) on mortality. For studies that looked at the effect of pure depression on ...
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A descriptive geographic statistics, or descriptive arithmetics question

[Please point me to a more statistical/arithmetical part of stack exchange if there is one. I can't find it] Country A has 16 million inhabitants and 2.000 MW of solar panel generated power, also a ...
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When is the best to add control variables in multilevel modelling?

Is it better to add control variables before or after the main predictor variable while conducting a step-wise multilevel model?
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Term for two variables that are “too close for control”

Sometimes we are tempted to assess a relationship of X1 with Y while controlling for X2, but it would be a mistake, because X2 is not merely correlated with Y -- it is more closely associated than ...
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Changes in significance and effect size (though constant SEs) when controlling for a categorical variable. Correlation test & interpretation?

I am interested in the effect of the extend to which an occupation consists of routine codifiable tasks and individual job displacement. I have individual level survey data and use a logistic model to ...
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do not need many controls with big data?

I am looking at a paper which uses a large panel data, 1 million observations, a dozen variables. I recall that in a discussion another one has the following comments: In structural models like ...
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Compare variable across two groups conditionally on a variable that has a strong correlation with the variable

I have the following scatter plot. I want to do a statistical test to asses something along the following lines: "are the red dots on average higher/lower, given the y-coordinate". But I don't really ...