Questions tagged [adjustment]
This tag is ambiguous and should be avoided.
152 questions
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ARIMA, adjustments and intervention analysis
I have very little knowledge of time-series analysis (despite my stat master - didn't do anything else than an introductory course) but now I'm facing a statistical problem whose answer is this very ...
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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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Methodological question: adjusting for confounders in logistic regression
I have three attributes in a dataset (D0), representing the binary response of success or failure (R), some form of treatment or treatment group (T), and a potential confounder (C) respectively. ...
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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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Adjustment in DLNM - case control setting
I have data in a case-control format with a 5-year lag of exposure. I want to adjust, in addition to the strata, for the number of monitoring stations used to calculate the exposure. The problem is ...
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Significance testing when the treatment group was only partially treated (an unknown set of individuals did not receive the treatment)
I have a somewhat messy experiment that has already been conducted with large test and control groups, and have measured the response variables (sales / individual, etc). A known percentage of the '...
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Adjusting variable for covariate to calculate rates or metric
In this report by Dartmouth Institute, rates of utilisation (per patient) were reported by year and regions. The input measure of utilisation were said to have been adjusted for differences in age, ...
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When is it appropriate to adjust an independent variable by regression before including it in a regression on the dependent variable of interest?
I want to run a linear mixed regression in which, basically, I see whether the expression of a particular gene is associated with a trait exhibited by the animal. I'll use growth rate as an example. ...
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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, ...
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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, ...
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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 ...
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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), $...
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Adjustments to (Linear Regression) Forecast
Full disclosure: I am not a statistician, nor do I claim to be one. I am a lowly IT administrator. Please play gentle with me. :)
I am responsible for collecting and forecasting disk storage use ...
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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 ...
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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 ...
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Is meta-analysis of odds ratios essentially hopeless?
In a recent paper Norton et al. (2018)$^{[2]}$ state that
Different odds ratios from the same study cannot be compared when the
statistical models that result in odds ratio estimates have different
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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 ...
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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
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Is it invalid to adjust my independent variable based on a regression model fit?
I have a dataset and I want to visualize the relationship between Outcome and Variable1, after adjustment for ...
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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-...
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How can I adjust values in a timeseries to account for effects from other variable(s)? i.e. using a GAM
I have a dataset of monthly air pollution levels (i.e. PM2.5) as well as a corresponding dataset with monthly rainfall amount (i.e mm) spanning several years. These datasets have moderately strong, ...
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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 ...
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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 (adjustment variable) should be a random effect, regardless of ...
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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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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 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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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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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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Adjusting P-Values of one-tailed tests
I am running a large number of two-sample Wilcox tests and using Benjamini, Hochberg, and Yekutieli method to adjust the p-values.
The issue is that when I conduct a one-tailed test, the p-values ...
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How to detect seasonality in data in R?
My goal is to (1) prove the hypothesis of seasonality in this inflation time-series and (2) remove the seasonality via the X-13-ARIMA-SEATS procedure.
My questions are (1) how does one prove such ...
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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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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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Adjust ROC analysis for multiple testing?
we did an exploratory prospective study in medicine in order to find parameters which are able to predict a specific post-surgical event (0/1) before the actual surgery. We have about 10 parameters ...
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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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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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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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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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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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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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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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