Questions tagged [adjustment]

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Linear Regression using aggregate variable create multicollinearity or adjustment issue?

my group project has a number of independent binary variables x1,x2,...,xm and a dependent binary variable y. My dataset contains some million of rows. Since there are so many independent variables, ...
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Adjusting for confounding in linear regression model

I am wondering how would the slope and intercept change after adjusting for a confounder factor. After adjustment, would the slope be lower, or higher, and the value for the intercept? Is there any ...
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The meaning of "ICC corrected by age and comorbidity is best described in detail"

I received feedback on a manuscript comparing the mortality of two populations. Both crude and adjusted mortality rates are compared. Adjusting was done for age and comorbidity score and it is clearly ...
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Calculate covariate-adjusted means and 95%CIs for treatment and control group separately for simple 2-arm trial

I have data for a simple 2-arm RCT, that looks as follows: ...
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Adjust for covariates in small sample size (IPTW, PS match, etc.)

I have a dataset of patients with a grouping variable (groups A (control) and group B (treatment)). The two groups have sample sizes of 170 vs. 30. I would like to compare outcomes between the two ...
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Which p-values do I use for FDR in 3 separate multiple linear regression models?

I'm trying to carry out Multiple Hypothesis Testing Correction using adjusted p-values (FDR Method) from my multiple linear regression models. I am testing 11 independent variables of interests ...
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Can you adjust for covariates that have minimal variability/sparse categories?

I'm trying to run a regression on the effect of HIV on sleep and I want to adjust for smoking (one of several covariates). So the model looks like: ...
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Adjusted between-group comparisons : single vs separate linear regression approach

Suppose I have 3 groups - namely, "3" , "4", and "5" - and I am interested in comparing group "3" with "4" and with "5" on a continuous ...
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Including pre-treatment covariates in difference-in-differences: what if my covariates determine treatment but are outcomes of treatment?

I have the following question: What should I do with covariates that affect treatment in the pre-treatment period but are affected by treatment once the treatment is in place in a difference-in-...
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How to adjust weight data for gender and batch

I have weights from mice raised in 10 batches. I want to adjust the weights for the gender and batch of the mice, so that I can select the heaviest and lightest for further testing. I know I can do ...
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Age-adjusted mortality rate given age distribution and total number of deaths

I am a bit confused as to how I can calculate age adjusted mortality rate given the two datasets that I have. My first dataset consists of covid deaths per city district and is a gross sum (...
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How can I deal with a covariate being defined only for a subset of my sample?

My model looks like: ROI_size ~ diagnosis + medication_dose + sex + age. Specifically, I want to find the effect of disease (1 or 0), adjusted for current medication dose (measured in mg) on brain ...
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Does machine learning methods adjust confounding effect of the variables?

I have implemented machine learning (RF) for analysis of a dataset, evaluating observations' survival. After analysis (including variable importance) one of my collegues asked me that does ML method ...
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DAG: interpretation difference of TOTAL and DIRECT effect in terms of adjusting

Could one explain in simple words how examining the total and direct effect differ in terms of adjusting? How to interpret the findings of these two approaches? DAG Minimal sufficient adjustment sets ...
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11 votes
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Would the real adjusted R-squared formula please step forward?

The following question, What is the adjusted R-squared formula in lm in R and how should it be interpreted?, presents different formulas for adjusted R$^2$, which were, Quote: Wherry’s formula: $1-(1-...
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Adjusting alpha for several models in which I am just using most variables to adjust

If I have a study in which I run four regression models, each containing 5 independent variables, this would result in 5*4 = 20 p-values. However, let's say the first variable is what I predict has an ...
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P-value adjustment for different classes each tested individually

Testing the effect of a certain gene on survival of two different but somehow related (brain cancer GBM and LGG) patients, with each cancer (GBM or LGG) having several subtypes, how should I adjust ...
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Why adjusting for randomization stratification factors in the model improves the precision of estimators for treatment effect?

I assume you will already get balanced treatment assignment within the randomization strata. Why would we still gain improvement in precision by adjusting for these factors in the model? Does not ...
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Should the choice of propensity score matching versus weighting depend on the degree of overlapping of PS distributions?

I heard some opinions that matching is no good since it excludes some subjects. However, if we use PS adjustment or PS inverse probability weighting, is there a requirement on the degree of ...
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Categorical predictor: difference between additive vs hierarchical adjusting

Let's assume that: we are interested in the effect of X1 on Y that our data suits well for hierarchical modelling different cities have different number of subjects in our data Additive model: ...
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DAG: are there situations where adjusting for mediators is reasonable?

One thing about DAGs keeps bugging me - are there situations where adjusting for mediators is reasonable? E.g. consider the experiment below, where a power-calculated sample of subjects participated ...
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How to adjust for a categorical variable in a way that its levels have equal weight in regression? (predictions are not for the reference category)

I hope I am not asking a stupid question :) Model salary ~ social_club + town Data ...
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Confusion with adjusting: adding all predictors into one model or running multiple models

I generally understand quite well the idea of adjusting; however, the current study design is killing me. Despite hours and hours of thinking (and my head almost explode), I still don't know, which ...
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Area and time adjusted counts

In 2019 I went to a site and counted 4 species of birds. The size of the site was 130 hectares and I spent a total of 54 hours counting the birds. The peak counts of the 4 bird species are presented ...
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4 votes
1 answer
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P-value correction for multiple testing using huge datasets

First of all I apologize without the question is very basic, I am taking my first steps in data science, statistics and bioinformatics. Data information We are evaluating the correlation (using the ...
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Not understanding adjusted p values with Holm's method. Highest value in series divided by 1

I'm finding an issue while adjusting p-values with Holm's method I cannot understand. It's not a problem in my actual data, but I would appreciate any help to understand the issue. To show the ...
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2 votes
1 answer
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Is there any consensus on adjusting p-values for multiple tests?

I'm confused as to when adjustments for multiple tests need to be used. I'm an undergrad who's familiarising himself with stats, so apologies if my question sounds dumb, but I haven't found any ...
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Multiplicity correction when using emtrends to see if slopes are different from 0

I have a relatively straightforward question but I haven't been able to find the answer. Consider this example: ...
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245 views

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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When do I have to correct for multiple comparison when computing different mutiple regression models?

I' ve got a problem with my thesis. I use a set of 3 bloodbiomarkers plus age as a covariate to predict Marker of Functional Connectivity on the one hand and Structural Connectivity on the other hand. ...
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4 votes
1 answer
253 views

Why match if you have the control data already?

I had a question about matching. I understand the benefits of matching prior to conducting a study due to potential increases in statistical efficiency/ adjustment for confounders. Let's say you're ...
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Comment on the change in p-value following adjustment for confounders

The Second Australian National Blood Pressure Study (ANBP2) was a prospective, randomised, open-labelled, blinded to endpoint (PROBE) trial of Angiotensin Converting Enzyme (ACE) inhibitors versus ...
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2 answers
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Adjust alpha when switching from one-tailed t-test to two-tailed

I started with a hypothesis that says e.g. A is larger than B which would usually call for a one-tailed t-test. But after acquiring the data it turns out that the effect seems to be contrary to my ...
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Matthews/Phi Coefficient on a 2x2 Contingency Table with Rare Positives

Suppose I want to measure the degree people like gold versus silver. For the sake of argument, let's say I have a contingency table like so: ...
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2 votes
1 answer
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Do I need to correct for p-value when doing repeated ANOVA test?

We are investigating the relationship between smoking status and the hormone level. Smoking status is X(three-level) and the level of the hormones is Y(continuous variable). However, the smoking ...
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2 votes
1 answer
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How to adjust a confounder in pre-post analyis

I have a paired-dataset of pre and post-surgery measurements of certain biomarkers. I have done a paired t-test to find if there is a difference in the levels of a biomarker, say x1, before and after ...
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1 answer
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Unadjusted rates vs. observed rates?

In poisson and negative binomial rate models, should the observed rate be the same as the unadjusted rate (in model with only 1 variable)? Should you report these unadjusted rates from a model with ...
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2 votes
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'hold constant' and 'adjust for', do these terms have the same meaning?

In the context of regression, is there a difference between saying you held x constant and saying you adjusted for x? Or are these exactly the same thing? Thank you!
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How to adjust P values for several Post Hoc tests

I have several continuous dependent variables x1,x2,x3, and one categorical independent variable x4 with 4 levels, I want to apply ANOVA for each of these dependent variables one by one and then do ...
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Ideal method for confounder adjustment

I have a fairly large dataset (15,000) in which I assessed the association of a three-level categorical risk factor to the outcome. The outcomes were significantly different for the three levels. ...
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3 votes
1 answer
1k views

Multiple minimally sufficient adjustment sets in a Directed Acyclic Graph (DAG): Which unbiased estimate should be presented?

Assume that you want to estimate the effect of $X$ (exposure) on $Y$ (outcome). A common question is: What variables should we adjust for in our model in order to get an unbiased estimate of the ...
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Data normalization (reward/penalization) in a learning paradigm

wondering if folks can offer guidance on this data normalization problem. When trying to determine retention of information after a time delay, the retention rate needs to be adjusted for # of items ...
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Need of p-value adjustment when analyzing all possible pairs of factor levels in linear model

I have a nominal (not ordinal) variable with $K$ levels (these are actualy some groups of patients) and I run linear model in which: this nominal variable is one of IV's (others are age, sex and so ...
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1 vote
1 answer
106 views

Using binary outcome variables in real-world data studies must be wrong?

Please be gentle if it's a stupid(ly easy) question: In medical literature lot's of randomised clinical trials use binary outcome variables, such as 90% reduction in Y, or Y<(a certain threshold). ...
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1 answer
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Known Correlation between predictors

I have two predictors and an outcome, let's call them x, y and z. I know that x and y are correlated with correlation r. I am trying to construct a linear model: z = ax + by + c I have an ...
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Highly significant t-test statistics, any way to correct this?

I have been performing several paired t-test, where I test whether the sample means are different between two groups. For all of my tests (approx. 30), which all carries 13-14,000 observations, I ...
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6 votes
2 answers
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Should all adjustments be random effects in a mixed linear effect?

I've been sometimes taught that when you are performing a mixed model, any variable of which you don't care about estimating a parameter (adjusment variable) should be a random effect, regardless of ...
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1 vote
1 answer
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Significance of correlation with range restriction in x

Background Range restriction can happen in various study designs and it affects the results of bivariate correlation or in multiple regression, for example. In some cases the range restriction may be ...
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1 answer
215 views

Deriving the values of the range around the mean value

This is part of a bigger quantitative reasoning assignment I was working on. My understanding here is that the upper bound and lower bound of the ranges for each of the exercises should be reflected ...
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1 vote
2 answers
2k views

How to calculate Mean adjusted by Covariate?

I need to calculate the mean of a variable, adjusted by another variable. Both variables are ratio scaled. I found this online: https://ideas.repec.org/c/boc/bocode/s344803.html which does what I want,...
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