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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Why do we do matching for causal inference vs regressing on confounders?

I'm new to the area of causal inference. From what I understand, one of the main concerns that causal inference tries to address is the effect of confounders! For the sake of reference, let's denote ...
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Percent Change as Predictor and Response variables?

I am interested in the relationship between magnitude of change between two correlated variables i.e., after training, if performance increased by X%, does the %increase in task 1 predict the %...
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Controlling for age in $t$-test

I have submitted a paper where I have performed a $t$-test between 2 groups A and B (coded as a dummy variable) to compare the mean of an Inattention scale derived from CFA analysis of the ADHD self-...
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Simple question of how models deal with control variables

Apologies for the very simple question, it's something I've had trouble wrapping my head around: How does a model (e.g. logistic regression) deal with control variables - if the purpose is to keep a ...
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Just adding control variable instead of Oaxaca-Blinder decomposition?

Let's say I am interested in the extent to which a wage difference between men and women is caused by different levels of education between men and women. I know one would typically use Oaxaca-Blinder ...
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Bad controls, Probit, and prediction

I have three related questions: For causal inference, does a variable that is an outcome of the variable of interest also need to be confounded with the outcome variable for it to be a bad control? ...
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How to "correct for" a categorical variable on an outcome

I want to compare the outcomes of individual subjects. This outcome changes systematically depending on the subject's location (e.g. it will always be lower in a certain location). I want to be able ...
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No change in the coefficients of my time-specific variables of interest when controlling for demographic effects

I have a balanced panel set and I study the following model: lm(value ~ task*jan20 + task*feb20 + task*mar20 + task*apr20 + demographic criteria), ...
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Anova-controling for age and gender

I have recently submitted a paper, and one of the reviewer rejected it since I did an ANOVA without controlling for basic demographics (age, gender) In my ANOVA, I have 3 groups : nascent, early, ...
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Difference-in-differences and control variables

Im currently processing a bigger assignment, and I'm trying to reproduce the following table, which are difference-in-differences (DD) estimates of income change on voter turnout. However, as far as I'...
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"Bad" control variables in randomised treatment trial

I am analysing the effect of a randomised treatment on several outcome variables. First i am interested in whether the treatment changes the first outcome (non-pecuniary value) by controlling for ...
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Extreme differences between control group and affected group

I am reviewing an article and cannot be overly specific but it involves one group of people with a medical condition and another group without it; the dependent variables are various mental health ...
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"Controlling for a variable" - can I predict from a Bayesian model having set a covariate to zero?

Someone once said that anyone who talks about 'controlling for a variable' probably doesn't understand statistics. I'm one of those people, alas. I've been using the R package Hmsc to build a spatial ...
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How to address control, extraneous and confounding variables?

I was going through a tutorial here and it has the below info "Controlling for a variable” means modelling control variable data along with independent and dependent variable data in regression ...
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Controlling for a variable almost the same as my moderator in interaction regression - colonial data question

I'm unsure of if i'm avoiding intermediate variable as controls in my interaction model, since the controls are fixed at the same time as the variable I'm adding in my interaction term. My model is as ...
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Controlling for a variable in Multiple Linear Regression

I´ve been performing a Canonical Correlation Analysis between two sets of variables (7clinical and physiological). However, it ...
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Control variable (country) in cross-sectional data

I have cross-sectional data like city country treated control1 outcome 001 A 1 123 12 And I want to run CIA based regression $outcome = beta0 + ...
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1answer
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Controlling for population size, using per capita or including a variable for population size

This question is based on the premise of a previous discussion: Is there a difference between controlling for population size directly vs. putting variables in per capita terms? I am curious if based ...
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In linear regression, is "controlling for a variable" implemented by one-hot encoding/dummy variable/design matrix?

The literal meaning of "controlling for a variable" is self-explanatory -- it means we want to "isolate" the effect of the controlled variable to study the effect of those "...
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Can Lord's paradox be caused by regression to the mean?

I am trying to understand Lord's paradox, where controlling for baseline status can affect inference. I tried to set up some data following the quotation in Wikipedia “A large university is ...
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What are appropriate covariates in ANCOVA? can you control for within-group variation?

I am comparing traits between pinned museum specimens and beetles collected in the field. So my independent variable is sample (historical/current). I'm using ANCOVA with sex and body mass as ...
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Retrieve random effects from an instrumented RE model

I am writing my term paper and I feel a demand to retrieve the individual effects from a Random Effects Instrumented Model (due to the usage of lags of regressors as the instruments, the panel is ...
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If I want to control for race in SEM, should I include race in the model, or should I run the model multiple times with 1 race category at a time?

I am running a SEM model. There is 1 independent variable, 1 mediator, and 2 dependent variables. All variables are continuous. I want to control for race (White, Black, Latino). To control for race, ...
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Can I use the principal components of control variables in regression?

I am running a logistic regression and one of my control variables is categorical with $100$ categories. This leads to problems because some categories have $3$ data points, out of tens of thousands. ...
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Variable controlling in linear regression and covariates

I am analyzing cardiac data and have interests in cardiac problems and exercise. I just want to focus on the exercise effect and found AGE is significant variable. I'd like to control AGE variable ...
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Linear Mixed Effect Model: Control for Continuous Variable that Changes with Condition

This is a neuroimaging study. I have a repeated measures study, where each subject has been scanned under two conditions (Movie1 and Movie2) (same day). I have measured how much they moved during the ...
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How to control for a variable (gender of participants) in GLMM?

I recently tested some participants on a navigation task. The success rate in the navigation task is a binomial record of pass (1) and fail (0). I assessed participants in different environmental ...
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Exploring long-term associations in STATA [duplicate]

I am looking at the long-term association between a diagnosis of depression and smoking status. I have data collected from the same participants at 2 points in time (i.e. 2 occasions). My data is in ...
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Choosing the appropriate statistical test

I am trying to examine the long-term association between smoking cannabis and a diagnosis of depression. I have survey data from 2 points in time for the same participant (repeated measures). The ...
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1answer
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Does convergent cross-mapping require you to control for other variables?

There's a really cool method called convergent cross-mapping (Tsonis et al. (2018)) that's used to see if two time-series are causally linked within a dynamic system. It seems really powerful and like ...
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Statistical test for comparing proportions of celltypes of patient cells between groups

I’m currently working on a project where I have to compare two groups, lets call them group A and group B. group A and group B are composed of cells, and have multiple patients contributing to each ...
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Residualizing dependent variable when only one group has the predicted value

I have a dataset with two groups. I want to control for a dichotomous variable (i.e. left/right) by residualizing the dependent variable regressing out the effect of the left/right variable. However, ...
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Cross-lagged model and supplement regressions: Do I have to include my control variables in the supplement regression analyses?

I’m conducting a cross-lagged panel model with 3 measurement waves. I include my two main variables (act, ese) and control ...
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How to control for variables in random forests (in R)?

I am using a set of life history traits and human impact factors (12 in total) to predict extinction Risk (binomial: threatend / non-threatened). My model is based on the default 'randomForest' ...
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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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1answer
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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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1answer
262 views

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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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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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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1answer
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Hypothesis test comparing proportions while controlling for the effect of a nuisance variable

I have data that looks like this: ...
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1answer
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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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1answer
626 views

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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1answer
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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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1answer
602 views

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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1answer
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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 ...