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

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4 views

Must Uplift model be limited to inverse scenarios?

Uplift models are meant to maximize return on investment on scenarios which takes into account positive respond even when untreated. the question is, must the 2-way model be inverse of each other ...
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1answer
28 views

PSM on panel data , R-square is low at (first stage) logit regression

I'm working on a project which embedded in a "PSM + DID" framework, namely, firstly use propenstiy score method to select camparable treatment and control group, ...
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12 views

Software that matches 6 groups by propensity score?

I have found MatchIt in R that does propensity score matching among 2 groups. But I have six groups that I'd like matched by age, gender, race, and a few other variables. They don't have to be ...
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19 views

Matching data before regression (multiple treatment variables)

I have the dataset for the health of patients along with various treatments they were given. In a normal case, I would just use linear regression to fit a model [y ~ t1 + t2 + t3 ... +tn]. This will ...
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1answer
23 views

Why is the log taken in the formula for weight of evidence?

Why is the logarithm used when calculating the weight of evidence (WOE)? For example, let bin i ($B_i$) have, 15% good 30% bad So good/bad = 0.5. Namely for each bad item there are 0.5 good in ...
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1answer
49 views

matched pairs in Python (Propensity score matching)

Is there a function in python to create a matched pairs dataset? e.g. ...
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4answers
128 views

Why does propensity score matching work for causal inference?

Propensity score matching is used for make causal inferences in observational studies (see the Rosenbaum / Rubin paper). What's the simple intuition behind why it works? In other words, why if we ...
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22 views

Propensity Score Matching w/ 3 levels Rx

I'm trying to match consecutive patients by fitting a Propensity Score. The treatment has 3 levels (Controls, Treat_1, Treat_2). The "MatcheIt" package, is designed to work only with 2 levels ...
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1answer
24 views

What does the notation 1{T = 1} mean?

Here's a screenshot: This is from Evaluating Continuous Training Programs Using Generalized Propensity Scores by Jochen Cluve, Hilmar Schneider, Arne Ulendorff and Zhong Zhao. I understand from the ...
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8 views

Creating products overall score across different data sets

I've created product score mapping that gets ranking for product according to reviews from different websites and in different contextual categories. There are 3 contextual categories: eCommerce/ ...
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2answers
71 views

Comparing two or more treatments with inverse probablity of treatment weighting

I am working on a cardiovascular observational study featuring three or more competing treatments. My preference would be to conduct the analysis first using 1:1 propensity score matching, for ...
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19 views

Getting the closest observations to a category

I've been thinking for too long on this already and I decided to socialize my problem to see what I can do. My set up is the following: the observations are already classified by a questionary (V1 to ...
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18 views

Recommendation for propensity score analysis text?

I'm considering purchasing a propensity score analysis text and welcome recommendations. I know the basics of propensity score analysis but would like an up to date reference guide & don't mind ...
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7 views

Coefficient of Quasi-Randomized Control Trial with different Treatment Intensity

I need some thoughts on the following problem which I have not been able to solve. I have thought of using different methods including OLS, FE, and PSM but I am not sure what to use. Here is the ...
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13 views

Any automation for non-stadnard distance for PSM in R?

Are there any packages for propensity score matching in R, that allow to use, say, Firth's logistic regression or Bayesian logistic regression estimates as a propensity score?
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1answer
28 views

Is Propensity Score Matching the Correct Tool to Match Cohorts by Disease and not Exposure?

For a set of patients that all underwent procedure A, is it valid to use propensity score matching to compare 2 subsets in which the patients have disease D (D+) to those that do not have disease D ...
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65 views

One to one exact matching in R [closed]

I'm attempting one-to-one exact matching in R. That is, I have 60,000 treatment observations and 200,000 control observations but I only want 60,000 control observations and I want those to be matched ...
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29 views

Propensity score matching - Force full match on specific categorical variable

I'm trying to perform propensity score matching using R MatchIt pacakage, and I have a question: I have tried the nearest neigbor method, and I understand that it tries to find the nearest match, in ...
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1answer
47 views

Categorical variable as control variable in MatchIt

I'm kind of new to R and trying to run propensity score matching using the MatchIt module. Some of my control variables are continous but some of them are categorical. For example, I have a "currency" ...
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10 views

Retrospective randomised study design

I would like to measure the impact of having/not having intervention (counseling) on lifetime cost of care. Patients all enter the ED, and some may be referred for counseling. In some cases, patients ...
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32 views

Propensity score - how to deal with panel data?

I am researching mergers and acquisitions. The overlying question is the following: Do companies acquiring targets in a merger wave (i.e. a period of time where abnormally many acqusitions take place) ...
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16 views

Test for Conditional Normality?

On page 357 of this article, it states: We assume that the treatment (or its transformation) has a normal distribution conditional on the covariates. How would I go about determining if a ...
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17 views

Treament By Covariate Interactions with Propensity Score Weighting

I am trying to estimate the causal effect of a treatment on an outcome using propensity score weighting. I estimated the propensity scores and verified covariate balance with a number of covariates, ...
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65 views

Propensity score matching in a longitudinal setting

I am using Stata 13 to investigate a local programm aimed at reducing obesity amoung teenagers and adolescents in a school. I have a balanced panel over twelve years and a couple of covariates (like ...
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13 views

A good way to estimate propensity score for IPTW (without linear dependence)?

Are there consistent estimates for 1/e(X), where e(X) is the propensity score, when no linearity assumptions on the dependence of e(X) on X are made?
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9 views

How to estimate discontinuous propensity score?

Are there any methods to estimate propensity score if its dependence on covariates is discontinuous? For instance, if there is a discontinuity on some hyperplane which is not known?
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47 views

DiD Matching with Time-Varying Treatment and Repeated Cross Sectional Data

I am conducting research on the effect of modularizationg (dividing courses in modules) on early school leaving (dummy variable where 1 = left school prematurely). I would like to match my treatment ...
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1answer
26 views

Is a comparison of patients between 2 clinics using propensity score matching a matched case control study?

I'm helping my boss design a study that will look at the effects of a clinic level intervention on a patient level outcome. I would like to look at the effect of our intervention on one clinic ...
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20 views

hlsens and match/genmatch giving very different results

I'm doing some propensity modelling in R using these functions: ...
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1answer
73 views

Optimal matching with caliper in MatchIt package in R

I am using the package MatchIt in R to perform propensity score matching. The command is ...
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2answers
68 views

Maximal logit distance for propensity score matching

I use propensity score matching (PSM) with logit regression distance. What maximal propensity score (ps) distance in each pair of the treatment and control individuals can be allowed? What maximal ...
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10 views

Models and features used to estimate the propensity score in financial services (Banking)?

I'm trying to figure out how to compute the probability of a bank customer converting after sending him an offer. After a lot of research i found that propensity scores is what i am looking for. This ...
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26 views

Propensity score matching linearity assumption

One of the advantage that i have herd talked about propensity score matching, vs. a regression, is that propensity-score matching doesn't rely on linearity assumptions. This seems incorrect on the ...
8
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1answer
385 views

The difference between average and marginal treatment effect

I have been reading some papers, and I am unclear about the specific definitions of Average Treatment Effect (ATE), and Marginal Treatment Effect (MTE). Are they the same? According to Austin... ...
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17 views

propensity match advice

I need some advice on how to tackle this problem. I have two groups (treatment n=30 and no-treatment 400). I want to match the treatment group patients to the other group based on comorbidities and ...
2
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1answer
34 views

Including already balanced confounders in propensity score model

I have a dataset that I want to run propensity score analysis on. Using package TWANG in R, I plan to compute the propensity score and use it as IPTW. The variables that I put into the model are those ...
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10 views

Obtaining matched data from original data using match.data command in MATCHIT package

I am using matchit package. For getting the matched data set, match.data command is used.But it is not excluding the unmatched and discarded cases. Please can anybody guide me regarding this.
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53 views

Interpretation of ATE for IPTW propensity score analysis

I understand how we interpret the average treatment effect (ATE) when we use propensity score matching. We match on propensity score, and then subtract away the groups to get the average treatment ...
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0answers
39 views

Pre and Post matching glm syntax in R

I am trying to compare the effect of breastfeeding on child outcomes using PSM in R. Breastfeeding is my treatment whereby mothers who breastfed are coded as 1(treatment) and those who don't as ...
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64 views

Optimal Bandwidth Selection for Propensity Score Matching in Stata

currently I am performing a DID ATT estimation with propensity score matching and I want to present estimates for NN-matching with 1 and 2 neighbors as well as kernel(gaussian)-matching with an ...
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2answers
70 views

Model Selection in Propensity Score Matching

I am trying to fit a logistic model to create propensity scores. Looking though the literature, there appears to be some disagreement on which covariates to include when designing such a model. Some ...
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0answers
62 views

Propensity Score Matching with few treated observations

Consider the situation in which one has 3000 untreated observations and 30 treated observations, that is, a ratio of 1/100 between treated and untread. In this situation, I believe the logistical or ...
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1answer
49 views

Validating a predictive model after using propensity score weights

I have observational data with a "treatment" and I want to use propensity scores to weight the samples. A predictive model will be built (including the case weights). I will want to include the ...
4
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0answers
156 views

Analyzing the effects of different scholarships among university students

We have a data set that has data on university students, including their socio-demographic characteristics (sex, first language, ethnicity, residency etc.), GPA and CGPA in each semester (note that ...
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31 views

Methods of Treatment Effect Heterogeneity Estimation (Observation Data)

Given observational data, where a "treatment" is chosen by the unit of observation or not, are there any standard methods of ascertaining not just if the treatment has effect overall (ATT), but ...
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119 views

matching one-to-many vs one-to-one?

When doing propensity score matching, how do you decide whether to do one-to-many or one-to-one matching? This paper says: "Increasing the matching ratio is thought to improve precision but may come ...
1
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1answer
88 views

Using Matching to Conduct a Sub Group Analysis

[Moved from stack overflow) While I have done a good amount of reading regarding the usage of PSM, I am still struggling a bit to see if it can be used in my application. I am trying to analyze the ...
0
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1answer
47 views

Standards for reporting propensity score matching

When publishing articles, there are international recommendations for reporting modeling such as the TRIPOD Statement (Transparent reporting of a multivariable prediction model for individual ...
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0answers
110 views

Conditional logistic regression or GEE in PS matched study

My situation: In a cohort study, I'm trying to find the correlation between outcome & Tx (Arm A vs Arm B). However, baseline covariates are unbalance between different treatment groups. Hence, ...
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0answers
87 views

Instrumental variable analysis after (propensity) matching

I am trying to replicate the methods used in this paper by Paul Rosenbaum and colleagues (Near-Far matching). I have been studying the methods in the referenced papers by Michael Baoicchi. My work ...