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

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38 views

How to do propensity score matching in R on a dataset of 10 million patients (won't fit into RAM)? [closed]

I need to do some propensity score matching. My dataset is way too large to fit into RAM, which I see as R's biggest problem right now. I see that the ff and ffbase packages are what I need. I ...
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30 views

Can anyone help interpreting this equation?

The following is a portion of text from the Heckman, Ichimura and Todd (1997) paper about propensity score matching in ReStud The matching methods discussed in this paper focus on estimating an ...
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1answer
42 views

How to create matched sample for sample selection method to perform?

I'm working on a project in which I only use sub sample (say the immigrant households of all households), and there is a sample selection problem that I apply the standard Heckman's sample selection ...
3
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1answer
123 views

Survival analysis: Multiply impute 5 datasets to average one propensity score then analyze OR pool the estimate from 5 imputed datasets?

I have a question regarding the use of propensity score in a survival analysis with use of mutliple imputation to handle missing data. The question is of theoretical nature and may well apply to other ...
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1answer
44 views

Combining propensity score matching with 2SLS

Inspired by the probit 2SLS estimation (see e.g. Wooldridge p.623, procedure 18.1 or check here probit two stage least squares), I am wondering if instead of running a Probit in the very first step, I ...
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55 views

Conducting Analysis after Propensity Score Matching

I want to perform propensity score matching of observational data of an Intensive Care Unit in order to find out wheather hydroxyethyl starch is better or worse than colloids in terms of renal ...
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15 views

For which data can propensity score matching be applied?

I wondered if besides controlled experiments (random distribution of treatments) and observational studies (treatment for homogeneous individuals), other settings apply for propensity score matching. ...
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82 views

Propensity score nearest neighbor matching with replacement and caliper

I am using the package MatchIt in R to perform propensity score matching. I have chosen to use nearest neighbor matching with a caliper of 0.2 and since in my case i have more cases than controls i ...
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21 views

propensity score matching: non-standard scenario

I have a time series of web transactions from a sequential test, i.e. there was no control. In other words I have the number of transactions before and after a change and want to evaluate the effect ...
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1answer
272 views

Confidence interval for average treatment effect from propensity score weighting?

I am trying to estimate the average treatment effect from observational data using propensity score weighting (specifically IPTW). I think I am calculating the ATE correctly, but I don't know how to ...
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74 views

Paired or not paired? Comparing groups after propensity score matching

After matching on propensity score, e.g 1:1 matching, you obtain a matched subset of your data. The built-in functions in the Matching package, as a prominent example, compares groups before matching ...
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95 views

Propensity Score Matching in R with Multiple Treatments

I commonly estimate Average effect of Treatment on the Treated (ATT) via Propensity Score Matching for a particular business use case. I'm currently using R, where ...
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60 views

Difference between marginal and conditional treatment effect? Relating to regression vs. propensity score methods

Peter Austin has a nice introduction to propensity score methods (citation below), and he states that one of the differences between PS methods and plain regression is that PS methods give you a ...
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56 views

Bayesian Network or Logistic regression?

The Bayesian Networks and Logistic regression can be used to predict events or give to each customer the propensity to have a behavior. Which are the advantages or disadvantages of these 2 methods? ...
3
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1answer
100 views

Propensity Score can be used as a covariate in regression?

I have treated and control groups with a problem of selection in the treatment group. I am interested in the identification of the following model: $y= exp(X^\prime\beta + \alpha\cdot T)$ where $T$ ...
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56 views

Observational data, matching, and resampling. Is this method defensible?

I am interested in comments on the validity (or not) of the following method for propensity score analysis. I’ll simplify the scenario a bit for clarity. I have 1000 subjects that received the ...
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31 views

Exclusion Restriction for Inverse Propensity Score Weighted Regression

I have been told that when fitting an inverse propensity score weighted regression 1) every control in the regression model should be used in the model estimating the propensity score, and 2) there ...
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43 views

Propensity score to match on exposure thats not a treatment

I have two questions on this subject: (1) The literature on propensity score (PS) consistently discusses the ability of PS to balance groups with different treatments. Does PS allow for balancing on ...
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93 views

PSM, Diff-in-Diff and Neg-logged income variable? How to interpret estimates?

I am estimating a difference-in-difference based on propensity score matching. The "treatment"-variable defines whether a household registered for a public insurance which was only active for two ...
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1answer
138 views

Interactions in Propensity Score Models

I am doing an analysis to see if a first-year seminar has an effect on student retention in college. Students choose whether or not to enroll in the seminar on their own, so it seems like it makes ...
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1answer
213 views

Nearest Neighbor Matching in R using matchit

I am using the matchit package to do propensity score matching on a data set. However, when doing nearest neighbor matching, if I use the caliper option, I get a different set of matched pairs every ...
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84 views

Propensity score matching by gender in stata

Hello Stack Community! I'm trying to do a matching in Stata. I need to do a propensity score matching between a single individuals dataset (men and women) to a couple dataset. What I like to do is to ...
2
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1answer
260 views

Propensity Score Analysis with continuous treatment

I have an observational dataset of about two dozen observed variables (continuous or discrete), plus a continuous variable of which I would like to measure the causal impact of on my dependent ...
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27 views

Multilevel propensity score

I'm trying to analyze many treatments on outcome after propensity score 1:1 matching. My problem: I have 6 differents drugs and each patient can take or not each of these. If I build my propensity ...
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2answers
348 views

Propensity Score Matching with time-varying treatment

The basic propensity score matching procedure works with cross-section data (ie collected at a certain point in time). The popular psmatch2 command uses a dummy variable indicating that an ...
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1answer
12 views

confound significantly different across groups

I feel this has to come up quite frequently, but there seems to be little clarity in how to handle the problem. If you have a demographic variable (e.g. age, edu) that significantly differs across ...
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5answers
599 views

Adjust for everything you have in propensity score?

I have a methodological question, and therefore no sample dataset is attached. I'm planning to do a propensity score adjusted Cox regression that aims to examine whether a certain drug will reduce ...
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196 views

Assessing quality of propensity score matching via covariate balance using standardised difference

I've been tasked with performing a propensity score matching and to measure the standardised difference for every covariate to assess the quality of fit. Details ...
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116 views

Propensity score matching: using alternative methods to create a distance measure

I would like to use a greedy nearest neighbour method to do propensity score matching. Though I've little experience here, it seems that the distance measure used is generally a propensity score ...
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102 views

Propensity score in time-updated (counting process) Cox regression

Suppose I aim to examine if treatment A is better than treatment B. My dataset consists of 10,000 individuals with a total of 100,000 observations. Thus each individual is observed 10 times and his ...
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197 views

propensity score with SPSS and R plug-in

I have recently installed R-essential and the "psmatching" program. All went well, until I performed (actually tried to perform) the analysis. Basically, I have a cohort of patients, divided into two ...
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1answer
157 views

Create age and sexmatched pairs to balance Cox regression further (updated)

I analyze ethnic differences in risk of cardiovascular events (CVD) in a cohort study of patients with coronary heart disease. It is known that immigrants have higher risk of CVD and I intend to show ...
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1answer
419 views

What is the equation for random forest?

I need an equation for random forest so that I can score fresh data I receive every week, based on beta estimates I got after building model using this ensemble methodology. Every week I do not want ...
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1answer
528 views

Accounting for Violation of Parallel Trend Assumption in Diff-in-Diff with Propensity-Score Matching

Objective: I want to test the effect of a regulatory change using a classical pre-post/treatment-control DiD design (Y = POST + TREAT + POSTxTREAT + e). Problem: Treatment & control obs. are from ...
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128 views

Propensity Score Matching – How do the mechanics lead to a different result than unmatched?

The gist of propensity score matching, as I understand it, is as follows: You want to estimate the average treatment effect (ATE) of a treatment on some outcome. However, if you simply calculate the ...
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49 views

Meta-analysis with known confounder

I’m performing a meta-analysis in which the main outcome of interest is a correlation coefficient between two variables, $X$ (a psychological measure) and $Y$ (a biomarker). $Y$ is known to be ...
3
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1answer
162 views

Infer causality with high collinearity

I recently started to ask myself how to measure the impact of education on indexes like GDP: what is the outcome of mathematics or computer science on GDP, at the country level for instance. In this ...
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1answer
159 views

Propensity score matching with multiple treatments

Is anyone aware of propensity score matching methods for when there are more than 2 treatment groups? I am working on a project with 4 treatment groups: A B A and B Neither A nor B Calculating ...
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0answers
348 views

Simulate predicted probabilities after a logistic regression

I'm generating predicted probabilities (propensity scores) in Stata using the predict command. The basic structure of my code looks like this: ...
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0answers
59 views

Statistical thought experiment (possibly Bayesian) about survey sampling and propensity scores

For some practical application I recently came about the following thought experiment. Can anybody help? Suppose we administer a survey A to measure a variable $Y$. The response probabilities may ...
5
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1answer
78 views

Accounting for post-intervention bias following propensity matching

Using a large, cross-sectional survey of victims of violence, I am interested in testing the effect of alcohol intoxication (let's call it the 'treatment') on victims' subjective rating of the ...
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2answers
135 views

Propensity Score

What are the various methods used for binary classification other than logistic regression? What are the advantages of logistic reg. model in developing Propensity score w.r.t. other methods? ...
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0answers
89 views

Propensity scores and patient comparability

I have two groups of patients who underwent a surgery using method A or method B. The first group are patients who were operated in 1980's and 1990's only with method A. The second group are patients ...
2
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0answers
384 views

Propensity score and Cox regression

I have a retrospective dataset of patients treated with a certain drug (treatment, $n=46$) or with placebo (control $n=96$). The stored variables are age, sex, stage of disease. I want to assess the ...
2
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2answers
265 views

Propensity score matching with zip code/geographical distance

I have a test group and a control group with a bunch of covariates; one of them is ZIP code. Is there a methodology that I can use to perform a propensity score matching based on ZIP code or other ...
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2answers
420 views

Understanding output of MatchIt in R

I have created a Matched Cohort using MatchIt package in R. I have the list of members who are in the treatment group and the control group. But I am unable to figure out which treatment subject is ...
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1answer
244 views

Propensity score matching using R

I have 50 control subjects and I would like to get 150 treatment subjects (i.e., a 1:3 ratio between the control and treatment groups) using propensity score matching and a few covariates. After ...
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3answers
11k views

Propensity score matching with panel data

I have a longitudinal data set of individuals and some of them were subject to a treatment and others were not. All individuals are in the sample from birth until age 18 and the treatment happens at ...
3
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1answer
97 views

Multiple imputation for variables used to calculate regression weights

My basic question: is there anything that you can't impute using MI? My more complicated question: Consider the regression $Y=\rho T+X'\beta+\epsilon$. For whatever reason, you want to weight the ...
2
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0answers
90 views

Heterogeneous Treatment Effects - How to test differences in the ATE?

I want to conduct a simple propensity score estimation where the treatment $D_i$ is a binary variable ($D_i=1$ individual $i$ participates in the labor market program, zero otherwise). I estimate the ...