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5 votes
1 answer
314 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
2 votes
2 answers
641 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
  • 21
3 votes
1 answer
3k 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
  • 2,267
2 votes
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
  • 773
2 votes
1 answer
490 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
  • 2,267
6 votes
1 answer
1k 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
63 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
1 answer
226 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
45 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
3k 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
  • 31.2k
0 votes
1 answer
301 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 ...
Prashin Jeevaganth's user avatar
5 votes
1 answer
3k views

Matching by or adjusting for confounders?

When using regression models with a binary exposure, how do you choose whether to adjust for a confounders as covariates or to match the two exposure groups according to the confounders and then ...
bobmcpop's user avatar
  • 1,333
1 vote
0 answers
81 views

Adjusting simultaneously for multiple confounders

I am having trouble understanding how to adjust for confounders in a basic statistical analysis. As a simple example, assume I want to know whether the weight of group of sick subjects and a group of ...
NewInstatistics's user avatar
0 votes
0 answers
231 views

How to adjust for confounding variables across different study periods?

I have a continuous & categorical outcome variables in three groups of patients, where the groups are defined by time periods 2010-2011, 2012-2014, 2015-2016. I found out that age and gender are ...
HNSKD's user avatar
  • 227
2 votes
1 answer
65 views

Unmeasured covariate adjustment

A study was presented where the authors used multivariable logistic regression to assess association between a risk factor and an incident disease outcome. The association was statistically ...
bobmcpop's user avatar
  • 1,333
0 votes
1 answer
2k views

How can i compare two groups by neutralizing age and gender?

I have two groups as control and study. I measured blood stem cell levels in each groups. I compared the levels with t-test between two groups and found statistical significance between two groups. ...
Karaca's user avatar
  • 9
1 vote
0 answers
758 views

How can I adjust for gender bias in age categories?

This is a hypothetical question about accounting for a confounding factor. I have an actual study but I'm not sure how best to explain, so I'm using a simplified example below. Apologies is this ...
Sam's user avatar
  • 11
3 votes
2 answers
24k views

How to "statistically adjust" for variables? [duplicate]

I've been trying to understand what means "statistically adjusted" when comparing two variables. For example, when computing the odds ratio for a death after surgery in two hospitals, we compute the ...
makansij's user avatar
  • 2,309
2 votes
1 answer
93 views

Adjusting confounders

I'm conducting a case-control study consisted of 32 males and 35 females matched by age and gender with controls. Do I have to control for gender when I do the statistical analysis?
Reem M.Al Haj's user avatar
0 votes
1 answer
336 views

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. ...
tohweizhong's user avatar
6 votes
1 answer
2k views

Does adjustement completely remove the effect of the confounding variables?

This might seem a silly question but I am really confused about it. In theory adjusting for a confounder variable should remove its effect. Is this always true? and does this mean that the effect of ...
JAMES A's user avatar
  • 61