Questions tagged [propensity-scores]
The probability of receiving a treatment given a set of observed covariates.
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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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18 views
Calculate treatment effect for an ordinal variable using R - matched data with MatchIt [on hold]
I have used MatchIt Package to match data using propensity scores.
Using the matched data, I want to estimate the Treatment Effect. My outcome variable is ordinal, and so I would like to calculate ...
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1answer
25 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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21 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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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
22 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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1answer
29 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
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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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1answer
29 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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41 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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26 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
17 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
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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
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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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Abadie Imbens (matching technique) number of observations: “nnmatch” command
I'm using the command for Abadie-Imbens matching "nnmatch". My co-author and I are wondering why the N resulting from this analysis is not smaller than the N resulting from using a more traditional ...
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32 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
54 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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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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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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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
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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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23 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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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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38 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
417 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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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
81 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
66 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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39 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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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 ...
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Propensity score weighting: Inverse of the probability this does not seem logical
I hope someone can help me understand propensity score weights. When weighting a regression (or other analyses) by propensity score one uses 1/propensity score as the weight which means 1/probability ...
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1answer
351 views
Nested Case-Control vs propensity score matching vs inverse probability when comparing differences in incident outcomes
I am not sure about the best design in this case.
I have a representative sample (N=15,000) of individuals with a moderately rare condition and I want to match them to controls who do not have this ...
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28 views
IPW for time-varying multinomial exposure
I am trying to estimate the effect of different variations of a treatment modality (A-->D) vs no treatment at all (E) using MSM based on IPW.
In this study, participants are seen every 3 or 6 months ...
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1answer
124 views
Low p-values in propensity scores
I am using the twang package to estimate the propensity scores of participants in two active labour market programmes. One of them is public works (with 20 000 ...
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Propensity matching and analysis of resultant data on a data set with repeated measures
We have extracted retrospective case-level data collected over several years. We are using the administration of rescue antiemetic in the postanesthesia care unit as a proxy for postoperative nausea ...
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Define population without introducing bias [closed]
I am working with a large amount of firm data where every variable is highly skewed as there are a large number of extremely small firms and a small number of huge ones.
I am interested in defining ...
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Cox Regression in Propensity Score Matched cohort after multiple imputation
I have a follow-up question on the question of this thread:
Manipulating data for propensity score matching following multiple imputation with mice package
In aforementioned topic we can see the ...
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1answer
83 views
Use propensity score or logit propensity score as distance metric for control group selection?
My question is a bit of a general one (and my first on here). I'm researching different matching methods for selecting a control group in an observational study, and when checking SAS's options for ...
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125 views
Generating frequency table and survival curve after multiple imputation
I'm using the MICE package to generate 10 imputed datasets. After that, I know I should perform analysis on each dataset (propensity score matching, Chi-square, and Cox-regression in my case) and ...
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232 views
Propensity Score Matching implementation after multiple imputation
There is a very good thread about Propensity Score Matching after multiple imputation with the articles referred:
Propensity score matching after multiple imputation
In the refered articles, they ...
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1answer
48 views
R: propensity match within range of continuous variable?
I'm working on a retrospective analysis on some oncology data using R. I'm trying to do a lot of the analysis myself.
My colleagues have used SPSS in the past and have asked me to specify limits for ...
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1answer
38 views
Theoretical question about post-matching analysis of propensity score matching
I have been developing a propensity score matching model, using logistic regression to model propensity, and I am wondering about recomputing propensity scores in order to validate a model. Here is my ...
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1answer
94 views
When propensity matching doesn't work
A clinical group presented a dataset based on a convenience sample of about $n=600$ patients in 3-groups, with roughly $n=200$ in each group. Like a lot of groups, the request was "we want to use ...
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3answers
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Do propensity scores reflect the probability of treatment or outcome?
I am a non-statistician PhD student working on a project that has involved some propensity score matching (PSM). I had initially assumed that propensity scores would represent the probability of each ...
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1answer
266 views
Own distance measure in R MatchIt
I would like to use propensity scores that I developed from a multilevel logistic model as the distance measure for matching using the MatchIt package in R. The documentation for MatchIt says that I ...
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32 views
An open database for propensity score matching
I need an open biological or medical database for benchmarking methods for propensity score matching. Where can I find some?
