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.
204 questions
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Interpretation of slope coefficient when a variable appears in multiple powers
In a multiple regression, how do you interpret the slope coefficient of a variable if some other power of the variable, say, the variable squared also appears as an explanatory variable, i.e., suppose ...
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How to compare 5 groups on categorical DVs with covariates in SPSS?
I’m new to statistics and working in SPSS. I have a 5-level categorical independent variable and several categorical dependent variables, some binary (yes/no), some with more than two levels. I also ...
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Compute difference in repeated-measures values, while controlling for another variable
In our experiments, we measured two types of metabolic rates - Baseline metabolic rate (BMR) and Summit metabolic rate (Mcold) on birds, such that each individual bird will have both BMR and Mcold ...
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Seeking advice on bad control when the relationship is indirect (overcontrol bias?)
I’m working on a project where we’re trying to estimate the impact of country fragility status on project outcomes. We have data on the total grant funding allocated to each project, which we’ve been ...
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Control variable on same level as fixed effect
There is a panel dataset with daily observations over two years and a control variable that changes on a monthly level and is the same for all units, so for all units within a month it takes the same ...
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Should All Variables Have Adjusted P-Values in Multiple Hypothesis Testing or Just Hypotheses-Relevant Variables?
I'm currently working on a project involving multiple hypothesis testing. I understand the importance of adjusting p-values to control for Type I errors, but I'm unsure whether I should adjust the p-...
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Change score as predictor
I want to see if a change in an independent variable (T2-T1) predicts another variable at T2. For example, higher increases in cognitive impairment over 1 year for people with dementia predict lower ...
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Multicollinearity when controlling for a variable
I have a few questions about multicollinearity in my data: I'm looking at a certain type of lesion seen on MRI scans; for each patient I know the volume of those lesions and a metric that captures the ...
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Impact of Covariates on ANOVA Results
I am conducting an analysis using ANOVA with covariates and encountering significant results. However, when I remove the covariates, the results are no longer significant. Here are the details of my ...
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Comparison of 2 groups with covariate
I compared 2 groups and found that their test scores are significantly different. However, I also found that they are significantly different in the mean age. I want to see if the scores between the ...
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Running a Negative Binomial Regression with Overdispersion
I am not an expert on SPSS but have been developing my skills and believe I should run a negative binomial regression on my data, though I am not certain.
I am testing the number of days people go ...
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Regression in sex differences multiple dependent variables
If I want to examine sex differences in three variables, lets say academic attainment, study motivation, and a variable that is categorical. How should can I fit these variables with OLS regression? ...
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Is every fixed effect a factor in the model?
Participants received one of three sets of instructions and each completed the same two unique questions in a randomized order. I have a 3 (instructions type) x 2 (question) mixed effects model with ...
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randomisation issue/crisis
I have randomized into three groups using a randomization aid and groups were examined at 2 time points. however in the analysis found that there was a significant difference at baseline in one of the ...
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Can covariates be included in multiple regression?
I am interested in understanding if two predictors variables are associated with treatment outcome (DV). I included two covariates that 1) differed across my levels of IV (age) and 2) another that is ...
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How can I show that none of the other variables in the model were potential mediators
Context:
I recently received a revision request for my research paper, and one of the reviewer’s comments was as follows:
"The authors should show that for any estimate from the linear regression ...
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Multicollinearity and control variables dilemma
I had some superficial understanding of multicollinearity, that two highly correlated variables in the regression model are not what we want, as the estimated coefficient would be biased.
Control ...
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Multilevel Modeling and Alternatives for Repeated Measures Design
I am conducting a study on the effect of different characteristics of urban space on human physiological response. The study is a "repeated measures" design. For this example, each of 5 ...
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How do I regress income quartiles against each other?
I'm looking to find out whether an attitude differs across income quartiles. My supervisor has mentioned dummy coding and regressing the quartiles against each other, however, I'm sort of at a loss as ...
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ANOVA/ANCOVA results in SPSS
I am unsure about how to interpret the output box I get doing an ANOVA in SPSS. That's the "Tests of between-subject effects" box in particular. I had 2 groups (A and B), and 2 results (...
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Is there a technique similar to multiple regression which does not require linearity?
Background:
We have biological gene expression data of cells (from a single-cell experiment). So, the data is in the form of a gene by cell matrix, where each value is the expression of a specific ...
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Is it meaningful to control for variables that are correlated with the independent and dependent variables?
Statistical training from the National Institute of Child Health and Human Development states:
A general (usually unquestioned) assumption is that differences on "nuisance" variables that ...
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Using interaction terms in causal models
I have the following model:
LOS (length of stay) = b0 + b1 Age + b2 Gender + b3 BMI
where Age and Gender are control variables, and my main IV is BMI. And this model isn't made for predictive purpose; ...
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What is an intuitive explanation for a lay-person why controlling for a collider is bad practice while controlling for a confounder is good practice?
Cinelli et al., 2022 and Wysnocki et al., 2022 describe in technical terms how controlling for a collider can lead to biased estimates. If one needs to explain why one should not control for a ...
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What is an “independent” effect?
According to one study by Wang and colleagues (2013), smoking cigars has “a positive and independent” effect on testosterone. What is an independent effect and what is the significance of one?
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When is "controlling for" effects nonsensical?
I am not as knowledgeable about statistics as I would like and I am looking for resources to help me understand what kinds of questions are meaningful and which are nonsensical. We are developing some ...
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Serial multiple mediated model in lavaan not calculating standard errors, Z-values, and P values for defined parameters
I am trying to run the following model in Lavaan, in which AM, RM, and CU are latent variables. It also has three control variables (CV1, CV2, and CV3).
I have written the code that is included at ...
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Controlling for a variable when estimating interaction effects
Consider the relationships among four variables: sex, activity, height, and ...
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Multiple proportion test
I want to test which week day is more important for a specific client, given a historical communication in different days and with open email or not . for example:
monday
Tuesday
Wednesday
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email
...
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According to DAG theory, why controlling for this variable doesn't close the backdoor path opened by controlling for the collider?
I have made the following model in DAGitty:
Where $X_2$ is controlled for.
DAGitty says:
The total effect cannot be estimated due to adjustment for an intermediate or a descendant of an intermediate....
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Including an interaction variable which doesn't vary within a key control variable
Let’s say we want to check the effect of the interaction of education level and gender of the salesperson on number of units sold by them. We have thousands of sales people in the data, but they only ...
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Is it a bad idea to use a variable that is strongly correlated with my independant variable of interest as a control variable?
I am currently looking into the correlation between academic freedom (my independant variable) and university rankings (my dependant variable) using OLS.
I find a negative significant correlation, but ...
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Logic of including an interaction term as a control variable?
I am reading a paper and it has the following simple model:
Y = a + b1 + b2 + b1*b2 + e.
The author seems to be interested in b1, not the interaction term.
How do we interpret b1 in this case? I'm a ...
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How to account for data's margins of error in a regression?
Apologies if this is too simple of a question. I work with population data from the census, which provides a margin of error for all their variables. Reviewers have asked that I account for the MOE in ...
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What makes a good control variable?
I am currently studying whether academic freedom (independent variable) has an impact on university rankings (dependent variable). So far, my model is only composed of these two variables, as well as ...
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How does R know which variable is the main variable of interest?
I'm starting to get a little confused about how R knows which variable is the main variable and which others are simply controls. For example, let's say there are three variables Y, X1, and X2, and I'...
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Controlling parents education that correlates with each other
I want to include both parent's education variables as control variables in my estimation about the effects of maternal bargaining power to child's educational attainments. They are stated as ...
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Does it make sense to "regress out on one variable" during permutation testing?
In our lab we have developed a non parametric permutation test which assesses whether a feature $f:G\to \mathbb{R}$ respects a given symmetric binary relation $A\subset G\times G$.
Regard $A$ as being ...
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Why add control variables in the second stage of an IV regression?
I am reading an article on the effect of income on energy choice (e.g., choice between traditional sources such as charcoal and modern ones such as electricity).
The authors instrument income with ...
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Difference between controlling for other variables in additive models vs. interaction model
In a regression model with multiple predictors, the word "control" is used to refer to the inclusion of other variables than the one relevant to a specific question (e.g., the effect of ...
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Controlling for individual differences in a repeated-measures design?
I have been analysing a study where around 500 participants each were given a survey, so there were repeated measurements of each participant. Participants were male and female uni students who were ...
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Dependent variable "controlled" by a binary variable?
in my research the DV should be measured by means of an intent scale (Individual Entrepreneurial Intent Scale). For "controlling" if the answer in DV is correct, I want to include a binary ...
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Can age ever be confounded if it is the independent variable in an observational study?
This is a follow-up to my previous question: "Basic understanding of control variables in observational studies"
I have understood the answer, but am still trying to figure out what I think ...
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Can we just "pre-test" the backdoor criterion?
I am trying to use DAGs to think more carefully about my regression models. I have a question about the "backdoor criterion", as usually seen in the DAG below (we are interested in the ...
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MANOVA (SPSS) test - determine control variables in moderation analysis
I am examining the moderating effect of IV1 in the relationship between IV2 and DV using hierarchical regression analysis. The study has 2 demographic variables: gender and age. To determine if it is ...
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Can we isolate the effect of two different control variables in a semi-partial correlation?
I know that we are able to use a partial correlation when we want to correlate X and Y but Z affects both of them and that we may use a semi-partial correlation when we want to correlate X and Y and ...
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How to study the impact of time in a mixed-factorial design?
I ran a study to compare 2 different computer interfaces (say A and B) meant to be used in an unfamiliar environment.
I want to compare:
How much effort participants took to complete a certain task ...
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Controlling for an effect by adding it as covariate in R
I have a dataset like this:
individual1
individual2
Bray_Curtis
Dyad_type
proximity
matriline
id1
id2
Aapi
App
0.47
1
0.14
1
1
2
Aapi
Eis
0.60
2
0.03
0
1
4
Potj
Popp
0.50
1
0.11
1
3
5
Aapi
Potj
0.27
3
...
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Basic understanding of control variables in observational studies
I'd like to understand the basic logic for control variables in observational studies.
According to Wikipedia, one should control for confounding variables, which "in this context means other ...
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Is there a formal methodology for controlling a variable in a tree based model?
I am currently building a xgboost model to classify data into 6 categories of risk for insurance policies. I have 5 years worth of policy holder data, including policy year. When building a GLM for a ...
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