Questions tagged [propensity-scores]

The probability of receiving a treatment given a set of observed covariates.

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Measuring Institutional characteristics and its impact on accounting information [closed]

How can we measure institutional factors that differ across countries while studying the impact of certain change policy change which affects that way companies is reporting financial as well as ...
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Discordant results using IPW and overlap weights (propensity score approach) in sub-group analyses

I am investigating the effect of a treatment on the risk of a disease (% disease=18.5% (515/2784)). To do so, I use a propensity score (PS) approach with two different weights methods: IPW (stabilized ...
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Adjusting the model by propensity scores after propensity score matching

I want to control multiple confounders in my data, and I have noticed that including the propensity scores as a variable in the model gives good performance after propensity score matching. I know ...
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Can I get simple Z-test results from PSM output?

I'm having a little trouble interpreting the data after a PSM match. I used full matching with a logit link, no caliper. I am testing my treatment "buyout" 's effect on the binary outcome &...
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Do you still need to include "site" as a random effect when modeling matched data set?

I am working on a multicenter propensity matched cohort study. The primary outcome is binary while the secondary outcome is continuous. First I performed multiple imputation to address the missing ...
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Bootstrapping necessary in IPTW? [duplicate]

IPTW as in inverse probability of treatment weighting. Currently I am working on a project investigating the ATT of certain antiviral, and I found out there are several stats papers on the necessity ...
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What else can you do with a a PSM balanced/adjusted sample?

I am using PSM matching in a paper I am working on. Prior to doing the PSM, I look at some summary statistics, including doing some t and z tests; buyout is the treatment, control is the control: My ...
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IPW model keeps showing different propensities

I'm trying to create an IPW model with a base model of MLP, yet from one run to another, all the propensity scores for each row in the dataFrame are distributed differently. Could you please help me ...
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Why is the V.Threshold showing "not balanced" - psm balancing

I ran a full match for a PSM, with the balanced output summarized below: ...
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Adjusting for drop-outs in survival analysis when all dropouts have time = 0 and event = 0

I have data where participants were assessed at two timepoints ; baseline and follow up. At baseline, participants were categorised based on presence of a marker (yes = 1, no = 0). At follow-up, ...
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Inverse probability weighting for right censored data in cox regression

I have data from a prospective study with two measurements per participant (baseline and follow-up). I am interested in whether a cut-off (binary) obtained at baseline predicts disease development at ...
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Subclassification on a propensity and prognostic score grid with k × k subclasses, using R MatchIt

I would like to perform a joint subclassification of some data on the propensity and prognostic scores as described in this paper "On the joint use of propensity and prognostic scores in ...
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Propensity score matching with replacement: setting a limit on number of reuses

We are using a propensity score model to built a control group in an observational study. We have tried several options and a 1 to 5 matching ratio with replacement ensures the best covariate balance. ...
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Stata teffects ATET

How does stata estimates ATET (Average Treatment Effect on the Treated) using teffects psmatch. I understand the average treatment effect (ATE) is computed by taking the average of the difference ...
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After using inverse probability weight, two groups are still significant

I used the inverse probability weight to eliminate the bias of demographics. After creating the propensity weight, I conducted series chi-square tests to compare demographic variables among treatment ...
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Is it possible to estimate IPTW in two different subgroups to evaluate interaction? (Subgroup Balancing Propensity Score?)

This questions needs a toy example to be explained. I apologize if the question is not clear. Suppose we have an observational study in which we want to evalute the association between exposure to ...
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Limits to how many control and treatment subjects may be paired in propensity score matching?

I'm working on a difference-in-differences project where we're matching up to 5 control subjects to each treatment subject using a combination of techniques to estimate treatment effects (ATT): exact, ...
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Propensity score matching sample size

I am considering doing a propensity score matching to evaluate the effectiveness of a intervention. However, i only have 193 cases in my treatment group. I have a lot in control group. My outcome is a ...
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Calculation for background characteristic of data sets that were imputed by mice and matched by MatchThem

I have performed multiple imputation in mice and created a dataset of 100 imputed data sets and then used MatchThem to perform propensity score matching. I can assess the balance of matched data sets ...
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IPTW in Cox Regression model using the WeightIt package - Question on ATT vs. ATE interpretation

I am currently trying to perform some IPTW adjustment in the context of Cox Regression models. I was interested in expanding my understanding of the differences between ATE vs. ATT estimation. I've ...
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Entropy balancing---how do we assess overlap?

I am familiar with propensity score weighting. I set up the propensity score model, and then generally check for balance and overlap in propensity score to ensure that assumptions are met. However, I'...
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Is propensity score matching out of favor? [duplicate]

I came across this post, which was largely nonsensical, but a respondent suggested the original poster follow up with two articles: Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching ...
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Regression discontinuity vs propensity score matching

I have recently read some pieces suggesting that regression discontinuity designs could be the best statistical approach for causal inference stemming from non-randomized studies (eg 1 and 2). However,...
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What is the positivity assumption required for matching and ATT estimand?

Does ATT estimand require a less stringent positivity assumption in matching? For example, if a small treated group is matched to a large control group, most of the control subjects will be discarded ...
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Choosing variables for propensity score matching

I'm working on a project dealing with transplants and comparing outcomes of first time (primary) transplants with re-transplants. I'm trying to decide which set of variables to include for propensity ...
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How to interpret covariate balance table for binary variables in inverse probability treatment weighting

A quick question on how to interpret balance measures in a IPTW analysis. Here is an example code from the cobalt package: ...
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Matching weights

I am planning to apply propensity score matching with exact marching on two categorical variables and balancing on the rest of my covariates. Are the weights obtained from the matchit function related ...
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IPTW and adjustment in Cox Regression Analysis [duplicate]

A question on how to deal with inverse probability of treatment weighted-Cox regression analysis. Basically, I am evaluating how to use IPTW in the context of survival (and specifically, Cox ...
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Inverse Propensity Score Weighting vs. Double Machine Learning

I am familiar with Inverse Propensity Weighting (IPW) for the estimation of causal effects, and recently, I came across the 2016 paper by Chernozhukov et al. on Double/Debiased Machine Learning. From ...
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How reliable is conclusion drawn out from a known data?

Most of time conducting experiment is expensive. Suppose I and my collaborator decided to use a known databank(NHANE, NCI's data) to do some digging with some untested hypothesis given. Most of time ...
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Propensity Score Matching with Covariates pre-treatment

I am applying a propensity score matching on R using the package Matchit. I read that to match the observations, you should take the covariates and balance them. However, only pre-treatment ...
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"If true propensity score is constant, then the superpopulation covariate distributions are identical in two treatment groups"?

This is a statement made in Rubin's Causal Inference Sec 12.5.1. I would take it under assumption of unconfoundedness framework. "If the superpopulation covariate distributions are identical in ...
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Nearest Neighbor Matching

This is probably a very basic question. But I spent a good part of 2 weeks trying to understand this (by reading textbooks, searching on internet, listening to lectures) but haven't gotten anywhere ...
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Propensity score matching in difference-in-differences

I have a data set in which I have treatment, event, and treatment*event vectors, along with other variable vectors that I have computed. I ran my regressions and find my coefficients and their ...
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What is the ATE in the output of stata with psmatch2 or teffects psmatch

It has been known that we can not get ATE from MatchIt package with method = "nearest" in R because What is the ...
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Prioritize variables in Matchit() R function [closed]

In the following matchit() example, I want to give more importance to (prioritize) matching Sales1 and ...
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1 answer
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How does the option"outcome" work in psmatch2 in Stata? [closed]

psmatch2 depvar [indepvars] [if exp] [in range] [, outcome(varlist)... in stata, I just learned psm, I have some doubts about the role of outcome(varlist). I found a psm example (with 3 outcomes), I ...
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Comparing mortality rates between two treatment groups [closed]

Would appreciate some insight on this. My aim is to compare mortality rates between two treatment groups (treatment A vs treatment B) for a given acute disease. The data goes back some 8 years (...
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Multiple imputation and inverse probability weighting for multiple treatment?

I am analyzing observational study data. My predictor variable is tg4 with 4 categories (0,1,2,3) and my response variable is dm ...
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Propensity score match with exact matching on one variable

I would like to compare survival outcomes of two groups (control vs. treatment). Because of imbalances of baseline covariates, I used propensity score matching using nearest neighbor matching. After ...
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Weighting data and causal modelling

When using causal models such as difference-in-difference or propensity score matching, will weighting the data to represent the population effect the outcome (i.e., will it bias my results)?
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When A/B testing is not possible

I need some methodological advice : I have a population which at a certain time received a treatment (I use clinical terms for practical reasons). I have then been asked what was the effect of the ...
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1 vote
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Using same control variables as in propensity score matching

I matched my treatment and control group in STATA, using propensity score matching. I also made sure that each treatment/control pair share the same industry and year ( it's a panel data). If I'm now ...
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1 vote
1 answer
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Interpreting ATT in PPM

I am attempting PSM for my observational study. I have created a propensity score, checked balance for treated and controls (using pstest), and used psmatch2 command in STATA. My outcome is mortality (...
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Interpreting regression coefficients for covariates after matching

I am new to the fascinating world of matching and propensity scoring. It is highly likely that I will be using some (or more) matching method(s) for my forthcoming project, probably with the R package ...
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11 votes
2 answers
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Is Propensity Score Matching a "MUST" for Scientific Studies?

Recently, I have been reading about Propensity Score Matching : If I have understood this correctly, Propensity Score Matching is used to construct control/treatment groups in scientific studies, in ...
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2 votes
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Feature Selection and Propensity Score Matching

After reading the section on variable selection in OHDSI for population-level estimation effects, I set out to add additional covariates to my process. As suggested, I began looking at implementing ...
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Should inverse probability weighting be used in two-way fixed-effects panel regression?

Let's assume a (balanced) panel data set with two measurement points $t_0$ and $t_1$, where $t_0$ may be considered as the baseline. Some of the ID's are treated at $t_1$, i.e. $D=1$, the assignment ...
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How do I properly run a propensity correction for a fixed-effects model in Stata?

I have a fixed effects regression with a highly unbalanced panel. I am recording the outcome for each day a person participates over the course of a fifteen year time frame. Individuals can enter or ...
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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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