All Questions
Tagged with propensity-scores matching
248 questions
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What are the differences between PS-match and adjusted Cox regression?
This is more like an extension of the following question: Propensity Score Matching with Cox Regression
I am wondering what are the differences between these:
matching patients with PS and running ...
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25
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Primer on Entropy Balancing
I've scoured the internet, but I can't for the life of me, find a comprehensive primer on entropy balancing.
I am currently in the process of cleaning data in order to create weights for the part of ...
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34
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covariate balance loveplot and distance
What is the distance parameter that is plotted on the love.plot ? I am not able to find any reference or explanation for this in the cobalt package. Any help understanding this value "distance&...
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42
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MatchThem and Mixed-Effects Logistic Regression in R
MatchThem and Logistic Regression in R
I am conducting a non-randomized study to evaluate the differences in complication rates between two treatments. The observed complication rates are ...
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51
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What should it be if the treatment group is larger than control groups in Propensity-Score-Matching (PSM) -DiD
In an effort to do Difference-in-Differences (DiD), to mimic the Randomized Controlled Trials, we normally use the Propensity Score Matching (PSM) to eliminate the difference between control and ...
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3
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2
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72
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Limitations of propensity score matching
While studying propensity score matching, I was struck by the following thought:
When we are running a logistic regression model to estimate $p(Z=1∣X)$ through some form of parametrization and we are ...
1
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49
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Statistical analyses after propensity score matching with matchit - Survival analysis- adjustment?
For an analysis of a data set I applied propensity score matching (matchit in R, 5:1, without replacement), which went very well- I dod not lose too much of the sample and got a balanced data set out ...
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62
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How to determine the treatment time for untreated in difference-in-differences design
I'm estimating the effect of treatment initiation on health outcomes using a Difference-in-Differences (DiD) design. The timeline is defined relative to the treatment date, not calendar time. For the ...
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20
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Propensity score matching - How to select observation for matching among repeated measures
I am unsure how to resolve the following problem and am hoping someone might have a suggestion.
We have repeated measures data for MS patients and we want to look at potential differences in an ...
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23
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(Propensity Score) Matching for multiple outcome variables
I have multiple outcomes (dependent variables) of interest. Before estimating the effect of receiving treatment on these multiple outcomes, I want to use propensity score matching as my control and ...
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Which kind of matching can i use and why doesnt my propensity score matching work?
I am currently trying to find out if a certain disease characteristic affects long term survival. I have observational data and i am trying to match my cohort, as there are huge baseline differences ...
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2
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140
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What are the possible solutions for performing full matching on a dataset with a size of 61,000? [closed]
I am working with a dataset of approximately 61,000 observations (with 27,686 treatment and 32,405 controls) and need to perform full matching using the MatchIt ...
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141
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Use SMD or raw difference in proportions when comparing balance of binary covariates used in propensity matching?
I am a junior in the medical field, and have been tasked with performing a propensity matched analysis of some data, using R.
I am looking at comparing the balance of my covariates (both before and ...
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18
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Matching on actual earnings versus matching on the kind of unexpectedness in earnings
For simplicity, lets assume this is a question about linear modeling, although I am actually looking at some non-linear models and am willing to consider other models if they would be more ...
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2
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47
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General question about exact matching on variable/s
I haven't used matching a lot but have certainly read many papers (some quite old and obviously before propensity scores were used much) that have talked about 1:1 matching on age, sex, etc variables ...
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272
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In propensity score matching, is the estimand to be estimated the ATE or the ATT?
In the propensity score matching literature (Central Role of the Propensity Score by Rubin), the treatment effect estimand is referred to as the "Average Treatment Effect" (ATE). However, in ...
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2
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63
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Propensity score matching with near-perfect differentiation
I am working on an analytics task for my job to match control units to treated units to monitor the effectiveness of a new marketing initiative. We decided to use a propensity score matching method ...
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108
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Assessing whether the probability of being assigned treatment is equal (or reasonably close) between two individuals/groups [closed]
I'm currently studying the textbook Design of Observational Studies, second edition, by Rosenbaum. Chapter 3 Two Simple Models for Observational Studies says the following:
3.1 The Population Before ...
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3
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1
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165
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What are the main pros and cons of the most commonly used weighting methods?
There are many methods to generate balancing weights in observational studies (see, for example, the many methods implemented in the amazing WeighIt package).
I have seen some great discussions about ...
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82
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Propensity score matching R swap control and treatment
I am analyzing observational data and want to perform propensity score matching. I would like to compare males and females matched for age,smoking status, bmi, etc. When I coded the male gender as 0 ...
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21
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How to Evaluate Interaction Effects in Propensity Score-Matched Samples:
Suppose I want to study the association between an exposure X and outcome Y, and I have used the propensity score to match each exposed subject with those unexposed but with similar characteristics ...
- 347
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62
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Propensity score matching - within subsample analysis
I am trying to understand the impact of a graduate degree in mathematics on the wages of students compared to other degrees. I have been running a probability score matching model using a logarithm ...
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1
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42
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Do I have to use the exact same variables in each step, if I have a two-step propensity score match followed by a regression?
I am using the propensity score match to grow my sample based on a smaller dataset of existing units that received the treatment. The match will find more likely units from its large population that ...
2
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1
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111
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How to obtain the (weighted or unweighted) L1 imbalance measure for "raw" data
I have two questions regarding the JASA paper, Multivariate Matching Methods That Are Monotonic Imbalance Bounding, by Iacus et al. (2011), the authors produce Figure 2 (left panel) where they compare ...
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38
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Should I use independent- or propensity score matching?
I work on data form an observational study (n=34) and want to compare the outcome of the individuals to an historic cohort (n=600). Subjects in the observational study received additional treatment ...
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36
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estimating effect with marginaleffect package
I want to estimate ATE. first of all I used MatchIt package for full matching for propensity score and then I used logistic regression with all of variable in propensity score model after that I used ...
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64
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Estimating treatment effect with G computation
I used the following code to obtain ATE. Before using the 'marginal effect' package, I examined the coefficients of the model and noticed that the 'symptom' variable has a high standard deviation. Is ...
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29
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When to calculate Outcome value in Propensity Score Matching with staggered adoption?
Sorry if this is a basic question (I'm no statistician): In a propensity score matching study, WHEN do you calculate the outcome values (for each treated and control unit) needed to compute the ...
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52
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Does propensity score matching reduce OVB?
Suppose you have data on a large population, a small proportion of which is treated. Let's assume there are enough treated data points that you don't need propensity scores for data reduction. There ...
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2
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1
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89
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Matching order based on grouping variable
I want to match in a certain order.
I am aware of the argument order, available in package {MatchIt} - but this refers to the ...
- 171
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57
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Matching approaches: hard match with propensity score (or logit) or hard match followed by propensity score matching
I have a population-based cohort and am exploring between two approaches to 1:1 matching:
Hard matching that includes the logit of the propensity score (one step)
Hard matching then creating a ...
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164
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MatchIt reusing control units multiple times in a panel data setting
I have a panel data with treated and non-treated firm year-quarters, and I would like to do propensity score matching to generate a treated/control firm subsample. The matching needs to be 1 to 1 and ...
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47
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Can propensity score matching be used in nested case-control study?
I'm poor with epidemiological methodology and I'm working on a study that look at the effects of a binary exposure on three time-to-event outcomes in a large cohort (general population). As the ...
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3
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1
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49
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Propensity scores with past observations
Theoretical question here: is it possible (and justifiable) to do propensity score matching when all control units come from a different time period?
For example, imagine there is a programme for 18 ...
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1
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266
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Paired or unpaired tests after using propensity score matching [closed]
I used propensity score matching in one of my studies to reduce the effects of confounding.
Although some authors have suggested that methods of inference appropriate for independent samples can be ...
- 159
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48
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Propensity Score Matching on Pre-treatment Covariates
I plan to do a propensity score matching and then do a Difference-in-Difference design. I'd like to only match using pre-treatment covariates. However, when I use the MatchIt package in R, I could not ...
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2
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96
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How to use Kernel weighted PSM and IPW in Triple Difference estimator (ika Difference in Difference-in-Differences)
I have learned a lot from @dimitriy answer in this post: Propensity Scores Weighted DID
I am currently utilizing the triple difference estimator for estimating treatment effects (please see the paper ...
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3
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1
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823
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Propensity scores: Variable K:1 matching with caliper- some technical questions (MatchIt, cobalt)
I have a data set from a cohort comparing two treatmens which I want to balance via propensity score matching.
I read some literature and decided to use a variable K:1 matching because this seems to ...
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2
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1
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375
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Log-Rank Test After Optimal Pair Matching
I have clinical data and used optimal matching in the MatchIt package to match cases to controls on several variables. Matching was done in a 1:1 ratio, and balance was achieved.
I then did a Kaplan-...
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1
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1
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482
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Difference between normalized difference and standardized mean difference in cobalt?
In Imbens & Wooldridge (2009, p. 19), they define the normalized difference as:
whereas the cobalt's package standardized mean difference uses by default (for the ATE) "the 'pooled' standard ...
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0
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1
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360
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PSM Propensity Score Matching Combination of exact and full matching
I would like to compare two groups (one treatment group and one control group). In both groups one can identify three different subgroups (let's call them Index-subgroup). I would first like to ...
user389026
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1
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64
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Extracting matched sample dataframe from MatchThem [closed]
I am using the R package MatchThem to match a dataset that contains 19 control samples and 13 case samples.
After running the ...
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0
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1
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261
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Log-Rank test with propensity score matched data
Let's assume that I have two groups that I would like to compare in terms of death rates. One group (group A) got a specific treatment and the other group (group B) did not get any treatment. I ...
user389026
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1
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783
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how to understand the weights in PSM？
When using propensity score matching or weighting, a column of weights is generated that is used to estimate the effect of interest.
According to a blog I read, there are three types of weights ...
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Is this sample size big enough to analyze with Propensity Score Matching?
Suppose I have a dataset where 9 patients occured with the post-operative complication.
(e.g. information such as height, smoking, weight, age, disease status) and rest of the 150 patients without the ...
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2
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1
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697
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Using Propensity Score Matching to Reduce "Class Imbalance" Biases?
Suppose I have a dataset where 100 patients have the disease (e.g. information such as height, smoking, weight, age, disease status) and 10000 patients do not have the disease (i.e. class imbalance).
...
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176
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matchit: Specified caliper still matches everyone!
Suppose we are using the matchit function from the MatchIt package in R, as in the following example given in the package,
...
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226
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How to model an interaction in a propensity-score matched dataset
Suppose I am performing a propensity score matched analysis using the MatchIt package in R, following the example reported here: https://kosukeimai.github.io/...
- 706
2
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1
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321
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How do matching/weighting outperform regression adjustment for making causal inferences? [duplicate]
In reviewing my notes about making causal inferences under the selection on the observables identification strategy, I reviewed some pieces that make critiques against contemporary strategies in ...
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63
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Propensity-Score Matching - what's the best choice when matching?
I'm using matchit package to create a propensity match.
I'm trying to match control and treated with a 2:1 ratio in order to maximize the population and exclude ...
