Questions tagged [risk-difference]

The risk-difference is the difference between the probabilities of an event under two conditions (ie, p1-p2). The RD has a possible range of [-1, 1]. It is a common measure of effect size in biomedical research.

The risk-difference is the difference between the probabilities of an event under two conditions (i.e., $p_1-p_2$). The RD has a possible range of $[-1, 1]$. It is a common measure of effect size in biomedical research.

In a typical study with two categories (say, treatments), and two outcomes (say, relapse or not), the data can be represented by a 2x2 table:

            outcome1   outcome2 
treatment1      a         b  
treatment2      c         d  

The risk-difference is estimated by:
$$ \text{RD}=\frac{a}{a+b}-\frac{c}{c+d} $$ Many practitioners prefer the RD because of its immediately accessible interpretation. When the treatment is unrelated to the outcome, RD = 0. When outcome1 is more likely given treatment1 than treatment2, RD is positive, and when it is less likely, RD is negative.

Note however, that the magnitude of a change of a fixed increment is typically not constant irrespective of the base rate. That is, increasing from 1% to 2%, or 98% to 99%, is typically not the same as moving from 50% to 51%. For this reason, the RD is often used when the probabilities are in the 'mid-range', but the relative risk is often used instead when the probabilities are quite small.

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Bootstrap for random effects logistic regression to get CI for difference in proportions

Let's say I have two observations of a binary variable per patient on two different treatments for a sensible number of patients, some variable like age, and I'm fitting a model like this in R: library(lme4) library(tidyverse) logit = function(x)…
Björn
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Is there any better alternative to Linear Probability Model?

I read here, here, here, and elsewhere that linear probability model (LPM) might be used to get risk differences when the outcome variable is binomial. LPM has some advantages such as ease of interpretation by simplifying the estimation of risk…
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odds ratio: the purpose and interpretation

Could someone please explain the purpose of the odds ratio and how it could be interpreted (i.e., the origin of their usage is in primary interest for me)? Why don't people simply use the difference between two proportions instead of odds ratio?…
user70810
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Using patient characteristics to predict disease and confront with per hospital real cases

We have a large, nationwide prevalence study about the prevalence of healthcare-associated infections (HAI). We need to see if hospitals have more or less HAI than expected by their patients' characteristics. We estimated the per-patient HAI risk…
Bakaburg
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Calculating risk difference and number needed to treat from hazard ratio in meta-analysis

If you have primary data, there exist several ways to calculate a risk difference (RD) or number needed to treat (NNT) from time-to-event data (see e.g. following pmid: 29955580, 31626655). However, I am performing a meta-analysis yielding a…
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In a meta-analysis, can you back calculate estimated group proportions from risk difference?

In a meta-analysis of the risk difference, does it make sense to apply the weights & back calculate the expected proportions in each group? For example, if you had the following: Study RD [95% Conf. Interval] % Weight …
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Two methods to calculate the confidence interval for number needed to treat yield different results

Assume that two drugs were tested. The risk of death for drug 1 is $p_1$ and the risk for drug 2 is $p_2$. We define: Risk difference (RD) $RD=p_1-p_2$ The number needed to treat (NNT) $NNT=1/|RD|$ If we know the estimated RD as RD* and its…
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Adjusted risk difference and negative confidence interval

I was reading this article. The authors used mixed effects logistic regression and presented their results as adjusted risk difference. I noticed that some of the confidence interval were negative, I was wondering if it is because risk difference is…
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Risk difference with patient-years incidence rates

I am aware that you can compute risk differences as the difference of risk between two treatment arms $( (\text{No. events}_1/ N_1) - (\text{No. events}_2 / N_2))$. However, can I estimate the same using patient-years incidence rather than just…
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Is there a minimum variance for metafor::rma.mv()?

I want to run a three-level meta-analysis model of observed data with Measurement as a nested level of Study (independent samples, only source of covariance being the study group measuring them) using the metafor package in R. However, when I try to…
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Why do we use the equal-means assumption in estimating the SE in a z-test but not a t-test?

When we perform a z-test for the difference in proportions between two groups of binary data, we use the fact that under the null hypothesis the proportions are assumed equal in order to estimate the SE. Suppose we have $\hat{p}_1$ and $\hat{p}_2$…
NeB
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Absolute risk and NNT from logistic regression

I fitted a Logistic regression with a number of variables, and was asked about the absolute risk (AR) and number needed to treat (NNT) for one of the variable with the outcome. I understand how to calculate them in a 2x2 table, but I am wondering if…
Inji
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risk ratio and risk difference consistent?

how do you determine whether the results for risk difference and risk ratio are consistent? Risk difference = 0.02, 95% CI [-1.05, 0.1] Risk ratio = 1.1, 95% CI [0.82, 1.5] Study on whether or not prior deliberate self-harm (DSH) is associated with…
Emma
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How can I estimate the risk difference confidence interval with the standard errors of the risks?

I have two risks estimated from imputed data, so I cannot say I have a1 events in the exposed and a0 events in the unexposed, as each data set is different. The output of the function are risks and standard errors. How do I find the confidence…
Alex
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Calculating risk difference with covariate

How do I calculate a risk difference for a binary outcome that takes into account a covariate? I want to compare accuracy of a skilled and unskilled tester at detecting 7 different types of tumors. Normally I would use a logistic regression with…
gecko
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