Questions tagged [propensity-scores]
The probability of receiving a treatment given a set of observed covariates.
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23 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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42 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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12 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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16 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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10 views
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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1answer
37 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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20 views
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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37 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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27 views
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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1answer
31 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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1answer
24 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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22 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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16 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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14 views
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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17 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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1answer
64 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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1answer
138 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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1answer
52 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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1answer
17 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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1answer
83 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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35 views
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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24 views
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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42 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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1answer
48 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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49 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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1answer
20 views
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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26 views
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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1answer
12 views
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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23 views
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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1answer
33 views
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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1answer
44 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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1answer
31 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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1answer
27 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
18 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
41 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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1answer
33 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 ...
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1answer
123 views
MatchIt: Explanation of Missing Factors from Summary
I am using the MatchIt package to perform matching between two groups (obese and not obese). The dataset that I am using has no missing data. I am matching on age, sex, and race. Sex and race are ...
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278 views
Probability calibration from LightGBM model with class imbalance
I've made a binary classification model using LightGBM. The dataset was fairly imbalnced but I'm happy enough with the output of it but am unsure how to properly calibrate the output probabilities. ...
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54 views
Confidence intervals after one-to-many matching - number of degrees of freedom
I have propensity score matched data after 1-to-3 matching. I am trying to use the code from the answer to https://stackoverflow.com/questions/37973240/
The question is: what number of degrees of ...
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86 views
Paired tests for one-to-many matched observations
I have a propensity score matched data after 1-to-2 matching. Each treatment case is matched to one or two control cases. May I use paired tests to compare the outcomes? The discussion https://www....
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2answers
91 views
Use of svyglm for a weighted regression in a bayesian framework
I am using the twang package in R to balance two groups by creating propensity scores, which are then used as weights in the svyglm for a weighted regression of the two groups.
I would like however ...
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30 views
Personalize Recommendations for small dataset
I'm working on a recommender system for a set of niche products. These are products that don't have a large number of customers. Does anyone have any tips on algorithms or approaches that work well ...
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40 views
Difference-in-Difference with multiple regression vs. matching combined with Difference in Difference
I want to use a Difference-in-Difference approach. In order to make sure treatment and control group are similar, I want to use a propensity score matching before the DiD approach. What I do is to ...
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42 views
How to quantify distance between 2 datasets?
I have a distribution $A$ (intent-to-treat population) and its subset $B \subset A$ (treated population).
I learn a propensity model $P(x \in B)$ to predict treatment.
Then I sample the intent-to-...
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1answer
669 views
propensity score matching with difference-in-differences for panel data
Research design utilizes companies that switched auditors (TREATMENT) and propensity score matched (PSM) companies that did not change their auditor (CONTROL). To obtain the propensity score for each ...
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20 views
Propensity score adjustment for multilevel exposure?
I have a hospital-based cohort study (n=1,275) and want to determine the effect of receiving a particular treatment during surgery to reduce blood loss (Treatment A), and receiving a blood transfusion ...
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1answer
89 views
How is instrumental variables with many exogenous predictors related to propensity scoring?
In a large (many exogenous predictors) instrumental variables regression, with covariate matrix $X$, outcome $Y$ and binary treatment indicator $T$, a two-stage least-squares approach might be like ...
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1answer
149 views
Using propensity score AND exact matching for control group selection
I am working with a team of researchers looking to select a control group out of a large population (150,000) to compare with a relatively small treated group (~900). We plan on using a propensity ...
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45 views
Propensity Score Matching and Outcome Analysis - Variable Use
If we match treatment and non-treatment people on a variable (e.g., gender), should we use that variable in the assessment of the outcome?
Let's say we match exactly on gender and approximately on IQ....
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2answers
320 views
In propensity score matching, should a variable used in exact matching also be used in the model?
In propensity score matching, we can match on variables exactly. For example, we can match males with other males only. Additionally, the variable can be specified in the model. Here's some SAS code ...
