Questions tagged [adjustment]

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When to use an adjustment method for Kruskal-Wallis + Dunn's and which method?

I need to do multiple pairwise comparisons among 5 groups (Treatment 1, Treatment 2, Treatment 3, Positive Control, Negative Control) for different tests and times. Each group has $10$ individuals, ...
Antonella's user avatar
1 vote
2 answers
42 views

How to handle factors related to the exposure but not the outcome

For example, the postprandial time significantly influences blood glucose levels, with higher levels observed when the postprandial time is short. Elevated blood glucose is a risk factor for stroke, ...
li jiaqi's user avatar
1 vote
1 answer
116 views

Why is CIHI recommending that we multiply the multiplicative error estimate by the per-capita rate?

I feel like this question is mostly about how to translate vague documentation into math than a statistics question per se, but please bear with me. I am reading the Canadian Institute for Health ...
Galen's user avatar
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Unbiased estimation of treatment regime contrast with time-varying treatment and outcome

I have some troubles finding a strategy to identify the causal effect I am looking for from my observed data. I am assuming the following DAG: where $Z$ is the result of a coin toss (randomization), $...
Denzo's user avatar
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1 answer
141 views

whether to adjust or not adjust for baseline in longitudinal RCT

I have a longitudinal RCT data, aiming to compare the superiority of one group with high exercising to the other group with low exercising to see the improving of pain (pain is outcome). Data is ...
user358238's user avatar
2 votes
1 answer
76 views

Should we adjust for this variable?

Four variables $X$, $Y$, $A$, and $B$ are assumed to have relationships as in the following diagram: Here, $X$ is the predictor and $Y$ is the outcome variable. Suppose that the research interest is ...
bluepole's user avatar
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1 answer
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calculation of cox-adjusted survival curves

In order to leverage a cox model for calculating adjusted survival curve - one must estimate the baseline hazard function. To my understanding this has to be estimated (non parametrically) for ...
Biased estimator's user avatar
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1 answer
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how to perform the pvalue correction in this analysis

How should I do the p-value adjustment for several post hoc comparisions. Should I adjust them all at once. Or should I adjutment per comparsion. Suppose ...
ElR's user avatar
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3 votes
1 answer
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Post hoc adjustment in clinical trial

I would like to make an adjustment on a baseline variable (which has a small imbalance).This is a post hoc adjustment (I recognize, however, the limits of this adjustment which has not been pre-...
Seydou GORO's user avatar
5 votes
1 answer
307 views

Is it a confounder on not?

I have a following picture and the assumption that I can estimate the effect of Treatment on Growth by accounting for dT. However, I'm not sure if Unobserved confounder is actually a confounder - it ...
Maria Li's user avatar
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1 answer
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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, ...
Ronald Carlos's user avatar
2 votes
2 answers
535 views

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 ...
COCONUT's user avatar
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1 answer
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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: ...
lethalSinger's user avatar
1 vote
2 answers
687 views

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 ...
Takanashi's user avatar
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0 answers
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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: ...
Hank Lin's user avatar
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1 answer
372 views

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-...
rodrigo franco's user avatar
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44 views

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 ...
user260878's user avatar
2 votes
2 answers
569 views

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 ...
nonsequitur's user avatar
2 votes
2 answers
1k views

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 ...
Behnam Hedayat's user avatar
3 votes
1 answer
2k views

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 ...
st4co4's user avatar
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11 votes
2 answers
1k views

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-...
Carl's user avatar
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2 votes
1 answer
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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 ...
Paze's user avatar
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1 vote
1 answer
63 views

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 ...
biofan's user avatar
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3 votes
1 answer
792 views

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 ...
hehe's user avatar
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1 answer
1k views

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 ...
hehe's user avatar
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1 vote
1 answer
76 views

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: ...
st4co4's user avatar
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1 vote
1 answer
798 views

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 ...
st4co4's user avatar
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2 votes
1 answer
447 views

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 ...
st4co4's user avatar
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1 vote
1 answer
38 views

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 ...
st4co4's user avatar
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1 vote
0 answers
22 views

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 ...
luciano's user avatar
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4 votes
1 answer
2k views

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 ...
Genarito's user avatar
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1 answer
721 views

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 ...
Miguel Menéndez's user avatar
2 votes
1 answer
148 views

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 ...
danjeff's user avatar
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1 vote
1 answer
873 views

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: ...
user3640617's user avatar
2 votes
0 answers
401 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 ...
Martin's user avatar
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2 votes
0 answers
17 views

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. ...
Hanne Schm's user avatar
5 votes
1 answer
952 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 ...
StatisticalPig's user avatar
0 votes
1 answer
61 views

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 ...
Bery's user avatar
  • 67
2 votes
2 answers
561 views

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 ...
Nilo's user avatar
  • 21
0 votes
1 answer
308 views

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: ...
Matthew M's user avatar
2 votes
1 answer
287 views

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 ...
JoZ's user avatar
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2 votes
1 answer
177 views

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 ...
arshad's user avatar
  • 863
0 votes
1 answer
65 views

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 ...
Nw2this's user avatar
  • 55
2 votes
0 answers
97 views

'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!
Nw2this's user avatar
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1 vote
0 answers
613 views

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 ...
Farid's user avatar
  • 83
0 votes
1 answer
42 views

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. ...
sjoh2574's user avatar
3 votes
1 answer
2k 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 ...
COOLSerdash's user avatar
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1 vote
0 answers
24 views

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 ...
umv5002's user avatar
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1 vote
0 answers
32 views

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 ...
Łukasz Deryło's user avatar
1 vote
1 answer
154 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). ...
sarapowell's user avatar