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

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14 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 ...
6
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2answers
82 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
6 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
155 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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1answer
31 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 ...
3
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0answers
53 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 ...
1
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0answers
27 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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0answers
31 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 ...
3
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1answer
80 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
89 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
77 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 ...
5
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0answers
81 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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0answers
25 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 ...
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0answers
73 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
109 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
224 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: ...
2
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0answers
54 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
54 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 ...
1
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2answers
109 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
70 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
197 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 ...
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2answers
185 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 ...
1
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1answer
173 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 ...
1
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1answer
161 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
6k 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
80 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
68 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 ...
1
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2answers
286 views

reconstructing matched data set from R's matching package

I am using Mebane and Sekhon's Matching package for R, and my goal is to make casual inferences about a proportion and a mean. The proportion is straight forward, but the mean has missing values, ...
10
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2answers
888 views

Propensity score weighting in Cox PH analysis and covariate selection

Regarding propensity score weighting (IPTW) when doing Cox proportional hazard modeling of time-to-event survival data: I have prospective registry data where we're interested in looking at treatment ...
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1answer
168 views

Using propensity scores from twang in coxph

I've used the twang package to calculate propensity score weights in my observational data set. The twang vignette uses the ...
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2answers
152 views

Is matching only for treatment effects with selection bias?

Propensity score matching (and other matching techniques) are used, as far as I have seen, exclusively for identifying causal effects of a treatment (intervention) and particularly where there is a ...
18
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3answers
2k views

Propensity score matching after multiple imputation

I refer to this paper: Hayes JR, Groner JI. "Using multiple imputation and propensity scores to test the effect of car seats and seat belt usage on injury severity from trauma registry data." J ...
2
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1answer
79 views

Account for group age differences

I have a dataset of two patient and one healthy control group which I would like to compare (using R) with respect to a continuous outcome variable (each subjects is measured once). However the groups ...
1
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2answers
138 views

How is it possible to turn out with a highly accurate prediction when all records were classified the same way?

We ran a CHAID decision tree model using the set up and process described in my related question here. We used the propensity scores to come up with a prediction. We measured the prediction at the end ...
1
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0answers
153 views

Predicting response propensity in a rolling data collection

I'm working with a survey that uses a rolling data collection format (i.e., there are multiple waves of sampling and initial contacts). I'm trying to develop a model to predict how likely a sample ...
3
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1answer
234 views

How to perform 1-to-1 matching when there are more treated than control subjects?

When there are more treated than control, is it possible to do 1-to-1 matching (without replacement)? It makes sense to do 1-to-1 when there are less treated than control but I am not sure if one can ...
2
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1answer
300 views

Is it appropriate to calculate odds ratios between groups matched on covariates (propensity scores)?

I have a data set that includes a primary dichotomous independent variable (e.g., smoking), a primary dichotomous dependent variable (e.g., chronic back pain), and several covariates (e.g., diagnosis ...
6
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2answers
2k views

Use of propensity score in a case-control study

The theory of propensity score (PS) suggests that it should only be used for the cohort study because PS matches the "treated/exposed" to the "un-treated/un-exposed" groups. However, cases and ...
4
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3answers
1k views

How to, or what is the best way, to apply propensity scores after matching?

I have developed a recent interest in propensity scores. I have been using the SPSS tool created by Dr. F. Thoemmes to calculate propensity scores using bivariate "treatment" variables (e.g., ...
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0answers
65 views

What is the relationship between propensity scores and sufficient statistics?

What is the relationship between propensity scores and sufficient statistics? I just came across the idea.
3
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1answer
367 views

Using ANCOVA with data matched on propensity scores

I've read papers comparing them, but never seen a study that used them together. Is this done? Why or why not? Suppose you use ANCOVA to analyze a reduced sample of matched pairs generated using ...
17
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4answers
5k views

How are propensity scores different from adding covariates in a regression, and when are they preferred to the latter?

I admit I'm relatively new to propensity scores and causal analysis. One thing that's not obvious to me as a newcomer is how the "balancing" using propensity scores is mathematically different from ...
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2answers
418 views

What is a good reference that discusses the problem of common support?

Asking this for a colleague: They have two groups of people with various characteristics and to address the issue of comparability of outcomes they would like to reference a paper or book that ...
2
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1answer
170 views

Aggregation of propensity scores with varying reliability

When trying to estimate the number of sampling units with an attribute, is there a good algebraic way to aggregate over propensity scores for that attribute which each have their own error? For ...
16
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4answers
2k views

From a statistical perspective, can one infer causality using propensity scores with an observational study?

Question: From the standpoint of statistician (or a practitioner), can one infer causality using propensity scores with an observational study (not an experiment)? Please, do not want to start a ...