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Questions tagged [propensity-scores]

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

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Propensity score matching with MatchIt: Question on missing standard mean differences in balance tab on cobalt package

I am using MatchIt to carry out some propensity score matching, and then using the cobalt package to generate the balance diagnostic. The summary() command on MatchIt has a known bug where it does not ...
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28 views

IPW for the effect of treatment on treated with a continuous treatment

I've been banging my head against the wall trying to figure out how to construct inverse probability of treatment weights (IPTW) for the population average effect of treatment on treated (PATT) with a ...
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35 views

Why is Propensity Score called a distance measure as well?

I had to use Propensity score matching for my study. I used the MatchIt function in R and I studied what it actually does. I understand that the propensity score is calculated using Logistic ...
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Creating a Weighted Ratio Based On Size of Customer

I am attempting to created a weighted ratio/score for customers based on the number of support tickets they have entered in a time period against the number of units they have in service with us. ...
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15 views

Propensity score: which treatment effect is easier to infer?

I'm currently working on a study where the goal is to estimate the treatment effect of a binary exposure. I want to calculate the Average Treatment Effect (ATE), Average Treatment Effect in the ...
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45 views

Matching with Multiple Treatments

What's the best way to use matching methods with multiple treatment groups? I'm assessing the impact of an intervention on an outcome. For my first analysis, I used the MatchIt package (see code below)...
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25 views

Difference between covariates and treatment confounders in propensity score matching

Here, I have the definition of a propensity score: Propensity score is defined as the conditional probability of assignment to a treatment given a vector of covariates including the values of all ...
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43 views

Difference between using a propensity score for matching vs. regression analysis

So I am confused on what the difference is if I match patients based on propensity scores vs. using the propensity score and then applying that into a multivariate regression analysis? Is there a ...
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28 views

Is repeated propensity score matching over many 0-1-features a valid procedure?

I would like to do a simple linear model where the outcome $y$ is real-valued, but my data matrix $X$ consists of several hundred features that all are $0$-$1$-valued. The number of observations $n$ ...
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28 views

CBPS Package: PS changes by changing base category [closed]

I am using CBPS package. The treatment variables has three options. Therefore, a multi logit model is run through CBPS. However, the resulting propensity score changes by changing the base category. ...
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69 views

Propensity Scores: What is this estimator?

I'm reading The Central Role of the Propensity Score in Observational Studies for Causal Effects in order to understand why Propensity Scores work. I'm kind of new to this and I'm not understanding an ...
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35 views

Posterior distribution of ATE with Bayesian propensity score model?

I am using propensity score weighting (PSW) to estimate the average treatment effect (ATE) of some treatment $D$ on an outcome $Y$ with covariates $X$. I have seen several ways in the literature (both ...
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78 views

Warnings during propensity-score matching: 1: glm.fit: algorithm did not converge 2: glm.fit: fitted probabilities numerically 0 or 1 occurred [duplicate]

I am doing a propensity score matching(nearest neighbor matching) in R with simulated data and I keep getting the above warning messages. please I need help. The following is my code ...
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60 views

A difference-in-differences propensity score matching approach

I am facing some challenges using the DID.I have around 500 Items off which 100 are test and its very difficult to find a control group for DID, so I used PSM to find control group using nearest ...
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63 views

Stabilized propensity weights: intuition and ATT formula

The average treatment effect (ATE) of binary treatment T on outcome Y can be estimated using inverse propensity weights: \begin{equation}\nonumber \frac{\sum_{i=1}^{N}t_i\hat{\pi}_i^{-1}y_i}{\sum_{i=...
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37 views

Propensity score matching and DD over different event windows

I'm currently working on a project in which we are trying to investigate the operating (accounting) performance of seasoned equity offerings. To comprehend the endogeneity problem, we apply ...
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38 views

Impact of propensity model

I have built a propensity model, which gives out probabilities of a customer paying given a collection intervention using a xgboost model. The model has an AOC-ROC of 81% with an accuracy of 77% ...
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Variables to include in propensity score matching

I want to use propensity score matching to estimate how becoming a mother affect your health. I define you as a mother, if you in 2006 have children who lives at your home. Since paneldata i ...
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87 views

Is it correct to use paired t test after 1:2 matching?

Is it correct to use paired t test after 1:2 propensity score matching? How we can do this in R? I found the following link in SPSS (https://www.researchgate.net/post/how_is_paired_t-...
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Can selection bias be solved by including control variables?

Omitted variable bias can be solved by including covariates that are omitted. However, can selection bias also be solved by including covariates?
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51 views

Propensity Score Matching over time?

I have two surveys of households in the same metropolitan areas about the number of transit trips they took. I would like to compare the change in number of transit trips taken by households, between ...
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propensity score matching by disease and cox PH regression.. am I right?

Normally I understood propensity score matching is the way to match the treated group and untreated group. But I noticed some studies that used propensity score matching to match disease and non-...
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42 views

Propensity score matching: bias adjustment

I'm using propensity score matching to match similar individuals. I.e., I first estimate a propensity score (the probability of treatment conditional on some set of variables) and then match on the ...
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46 views

Inverse probability weighting (IPW) with positive and negative treatments?

I am studying the effects of the government intervention which can take two directions and is usually represented as follows: $Treat = \left\{\begin{matrix} & +1 (intervene), if state A\\ &...
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45 views

Using propensity score matching to find control group for Diff-In-Diff

I am trying out DID as part of coming up with a model to estimate the effect. Below is the scenario: I have around 2000 items for test group(Item count may increase or decrease). Challenge is to find ...
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54 views

Uplift modelling

I have been trying to build a uplift model which gives incremental probability of a customer responding to a treatment. I am thinking of using pylift library for my model, I had few questions ...
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R- trouble understanding how setting estimand to “ATE” is affecting matching in “Matching” package

I am working on a project where I am using observational data from patients and trying to find a causal relationship on how Treatment dose affects Patient recovery. Since the data is observational, I ...
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19 views

Incremental Probability apart from the propensity model

I have built a model which predicts if a customer is going to pay given some kind of intervention, say calls. The model is used to generate propensity scores for each customer and then the calling ...
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73 views

for a multinomial treatment and binary outcome, what is more appropriate, ATC or ATE?

I need help to choose between ATC and ATE for my analysis with multinomial treatment and binary outcome. In the example below taken from here, it seems that ATT does not sound well for multinomial ...
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211 views

How to do PSM with panel data using PanelMatch?

I would greatly appreciate if you could let me know how to use PanelMatch for my dataset. Unfortunately, I couldn't find it's manual so I don't know how to find which firms are matched, how to extract ...
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79 views

how to calculate manually propensity score weights for multinomial treatments where one of them is baseline

I want to get intuition into the calculation of propensity scores (PS) and inverse probability of treatment weights (IPTW) for a multinomial treatment using multinomial regression. One of the ...
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37 views

Do propensity score matching methods need to factor in the index date in a matched cohort context?

I am working on a comparative effectiveness study where we estimated the propensity of treatment between two groups and are exploring matching on the propensity score. The study period is long, ...
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276 views

1:1 nearest neighbor propensity score matching in R (MatchIt package)

I used 1:1 nearest neighbor propensity score matching in R (MatchIt package) to match samples from an experimental group with a control sample. I used the procedure described here: https://pareonline....
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Propensity score matching: covariate balance

I have one concern about propensity score matching's assumption. It seems that what propensity score is doing is to say that the choice of treatment depends on pre-treatment covariates. Suppose I am ...
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Model subgroup- and covariate-specific effects for binary outcome over time

I am currently planning an analysis, in which I try to separate the change in the level of a binary outcome into a subgroup- and a covariate-related effect. Let's say there are three kind of ...
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61 views

Calculation of propensity score using cox regression analysis

I want to assess the association of a treatment with survival time in patients. The background information of patients like age and severity differ between the treatment group and non-treatment group. ...
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74 views

Variance of ATE (Average Treatment Effect) from log-linked gamma model

I have matched my sample using propensity score matching such that each individual has an estimated propensity score of being assigned to a treatment group. Let $T_i$={0,1} be the actual treatment ...
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83 views

Propensity to pay modelling

I am trying to build a propensity to pay model given an intervention to a customer. Context: The population I am dealing with are customers who were supposed to pay some amount on a certain date ...
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Propensity Score for observations in RCT study

In theory what would the $e_i$ (propensity scores) be, for $n_i$ observations already randomized into various treatment groups ? I know $e_i$ (propensity scores) are calculated for $n_i$ ...
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pospensity score modeling with differences in differences

I want to use a difference in differences specification which groups the data together using propensity scores. To do this is it as simple as obtaining the propensity scores, then taking the ...
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how to estimate prognostic core for a continuous, multinomial, and binary treatment, respectively

Quoting David Hajage and Finbarr Leacy, respectively: "Introduced by Hansen in 2008, the prognostic score (PGS) has been presented as ‘the prognostic analogue of the propensity score’ (PPS). ...
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Assesing impact for rolling enrollment data

I'm running an experiment where some of the users are shown a new widget when they become eligible (some conditions that are unrelated to the experiment itself). I have a control counterfactual group ...
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In propensity score matching, what violations or implications may result from having fitted propensity scores that are not centered at 0.5?

I currently have a procedure doing propensity score matching, and I use the fitted propensity scores (obtained via a glm call) and match on those. It turns out that I have about 60-70% more fitted ...
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45 views

Why is it easier, and just as valid, to assess overlap with logit propensities?

I'm looking for an intuitive explanation of why the logit transformation gives us a better picture of the overlap in the distributions:
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34 views

Propensity Score Matching on demographic baseline

A client asks for a PSM on gender for their big dataset of >10000 cases. About 20 variables are supposed to be included, most of them binomial. They hypothesize, that a certain treatment has worse ...
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52 views

IPTW ATE Significance Test

Does anyone have any experience using propensity weighting schemes such as IPTW (Inverse Probability of Treatment Weighting) estimation? I have a model that uses IPTW to estimate the Average Treatment ...
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1answer
22 views

Evaluating propensity score matches- what to do when ratio of variances or standardized means of difference go to infinity?

I am working on a project where I am comparing the effects of a particular treatment on patients with other patients who didn't receive the treatment. As I am trying to replicate a randomized ...
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1answer
50 views

For the Match() function in the R package, “Matching”, what algorithm is used for propensity score matching?

In the Matching package in R, one can conduct propensity score matching if propensity scores are passed to the ...
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37 views

When and how to use withSampW in the function get.weights of the Package twang?

I am using Twang R package in my analysis but I have doubt as to when and how should I use or not use the function get.weights. The package documentation here and ...