Questions tagged [matching]

Matching refers to a process in experimental design in which observations are sampled in a systematic, non-random fashion to be analyzed more efficiently with special statistical methods.

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21 views

Mahalanobis Distance for Continuous and Ordinal Covariates

My dataset of home sales includes covariates such as square_feet which are continuous and others like num_bedrooms which are in <...
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Propensity score matching - time variant treatment

I have a question about propensity score matching for a panel data file. The aim of my study is to understand the impact of having the first child on the wage of women. My data goes from 2001 to 2018. ...
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Why does case matching introduce bias?

I was reading the paper Biases Introduced by Choosing Controls to Match Risk Factors of Cases in Biomarker Research by Pepe et al. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3464972/ where she ...
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Is it acceptable to combine matched datasets for regression analysis?

I am looking at how different treatments (3 different kinds of protection of an area, and no protection which is the control group) affect my outcome of interest (deforestation) - in particular, I ...
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How to calculate Standardized Mean Difference after matching?

The above question seems quite trivial. Calculating it by hand leads to sensible answer, yet this answer is not in line with the calculated smd by the MatchBalance function in R. See below two ...
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Matching with or without sample weights

I have data for a sample of firms indicating whether firms are treated, some covariates and a firm performance indicator that functions as dependent variable. The sample is weighted to assure it is as ...
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missing value in the binary outcome when performing the propensity score matching (PSM)

I'm doing the propensity score matching by using R studio. Sometimes I have missing value in the binary outcome, e.g., I wanted to see 'development of significant coronary artery disease (CAD) on ...
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1answer
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Coarsened Exact Matching Non Homogeneous Treatment Effects

I am using the coarsened exact matching (CEM) package in R. I'm trying to understand the non-homogenous treatment effects. I've attached what an image of the linear model looks like and the model ...
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Transforming Covariate Matrix to Mahalanobis Space

I am applying Mahalanobis matching and want to visualize it at a lower dimension with PCA. This post illustrates how the Mahalanobis distance can be seen as the distance between points with shifted ...
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If you match within clusters,do you still need to use a multilevel model?

I am reviewing an article. I can't share details because the article has not been published but, briefly, the authors studied people with and without a condition and looked at long term sequealae of ...
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Looking for feedback on matching and difference-in-differences analysis

I am looking to set up my data and I have a question about the matched-pairs approach. I have plans for how to setup my data and am hoping for feedback as to whether it is a good way to go. ...
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Matching biometrics with NHANES

Good morning everyone, I'm trying to figure out how to do some matching with NHANES datasets. Basically, I have a separate population of participants in a weight loss program, for which we do not ...
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Matching / Scoring in an Experiment, using instrumental variable (IV) regression for LATEs

Maybe this is better suited here, than in economics. I don't know and please excuse the Econ language, I cannot do any better. I did an experiment with random assignment to two treatment groups and ...
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Pairwise external evaluation of clustering with a contingency table

I want to evaluate the clusters pairwise based on this publication: https://nlp.stanford.edu/IR-book/html/htmledition/evaluation-of-clustering-1.html (I have the ground truth of the real labels) So ...
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Matching when there are missing data

In a treatment effects framework, I have a control and treatment group with some covariates on which to match (I'm using nearest-neighbor method). The control group has a no missing data, but some ...
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1answer
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Can I include variables used for matching in the post-matching estimated equation?

I would like to apply Coarsened Exact Matching (CEM) on my data to reduce the differences between the characteristics of the treated and those of the untreated. I was advised to do matching to reduce ...
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matching then fixed effects

I have an unbalanced panel over time. Agents are sometimes in the panel and sometimes not. The sample share of certain groups (e.g. females) varies a lot over time (little at the start, more at the ...
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Post propensity score matching analysis with panel data

I have a cross sectional dataset of firms that used a specific mode of entry (joint venture) to develop in a country. I matched those firms with a much larger sample of firms which only exported in ...
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Can matched samples be analysed using regression?

Is it possible to use linear regression to compare matched samples in an observational study? In order to try to eliminate confounding factors, two groups were matched on a number of background ...
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Can I carry out a Propensity Score Matching with a general population of 90 observations and a treatment group of 20?

My population consists of 90 administrative zones that divide the city. Of those zones, only 20 received the treatment. After carrying out PSM, I have 17 zones in the treatment group and 17 in the ...
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Is Coarsened Exact Matching superior to other matching methods in case-control studies?

When used successfully to balance the covariate distributions in the treatment and control groups, is it safe to say Coarsened Exact Matching (CEM) is the best method for finding an unbiased estimate ...
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Matching varying amounts of attributes for an user

Background: We are trying to build a system that ranks created content to match user's needs. We have 5 attributes to match for each user but varying amounts of attributes for each content (1-5). The ...
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Is it possible to use Heckman's correction before matching?

I'm interested in the way migrants vote compared to the rest of the population. To do so, I'd like to use a matching method (PSM, CEM..., with the treatment corresponding to the fact of being migrant ...
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Match sample to equal men and women in factor analysis?

I have a sample of 1567 autistic participants (m = 925, f = 642) who all completed a 75 question questionnaire measuring 'Systemising' or the drive to understand systems/patterns. For my ...
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1answer
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How to account for dependencies in survival analysis of PS-matched cohorts with replacement?

I work on data from a cohort study (n = 3100). We want to compare outcomes of individuals with a special condition (n = 300) and their matched controls. I estimated propensity scores and used genetic ...
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52 views

Is it possible to use a multinomial outcome after a propensity score matching?

I would like to use a propensity score matching (PSM) to evaluate the effect of a treatment T on an outcome Y. In most of the papers that I have read, the outcome is continuous: health expenditures, ...
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Person matching for statistical purposes

I'm a business analyst working on a job where we need to match person records from disparate data stores to create a single best record of that person. This record will contain identifying ...
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DIF: match sample randomly or by age?

I am carrying out a DIF analysis comparing the scores of men and women on a questionnaire. A preliminary ANOVA revealed that when comparing total scores on the test, there is a significant effect of ...
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Best way to analyze propensity matched cohort with small n

I have performed a 1:1 propensity match using R's MatchIt package giving me 50 matched pairs. My primary outcome is 1 year mortality, which occurred in 25 of the patients. I'd also like to analyze ...
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Why match if you have the control data already?

I had a question about matching. I understand the benefits of matching prior to conducting a study due to potential increases in statistical efficiency/ adjustment for confounders. Let's say you're ...
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1answer
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Why don't people report the accuracy, ppv, or npv of their propensity score models

I'm using propensity score matching to estimate causal treatment effects. I have been concerned about diagnostic metrics for my propensity score model. However... when I look at the literature, no ...
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Difference between IPTW and MAIC?

Could someone describe the difference between IPTW and MAIC methodologies for indirect treatment comparison?
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Propensity score matching of three groups after multiple imputation in R

We would like to apply a propensity score matching procedure on three groups (one control group and two treatment groups, e.g. using the TriMatch package). Since the data set has missing values, we ...
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1answer
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How does the CEM package (R/Stata) handle missingness on outcome variable?

I'm trying to understand how coarsened exact matching works when there is missingness in the outcome variable. I need to match observations on several predictors and then estimate different models ...
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Matching with panel data and time-invariant treatment

I have panel data with municipalities in years being the unit of analysis. I want to examine the effect of industrial mining on interpersonal trust on the municipality level. The social trust data ...
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1answer
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Matched cox proportional hazard models

I have a dataset in which we follow a cohort of healthy individuals at recruitment, and when an individual experiences the event we assign four matched controls to it by age, sex, and recruitment ...
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The appropriate match ratio between case and controls: the obsession with 1:5 [duplicate]

My intention with this question is to collect relevant references or literature for a recurrent methodological approach commonly applied in health research. The main question is: what is the ...
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Constructing ordinal variable for matching

I know for all the firms in my data how the R&D budget is allocated to three distinct groups based on how applied the research is. For example for firm X I know: 10% of R&D budget is spend on ...
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1answer
23 views

Add samples to given set to match distribution

I have a distribution from which I can draw random (iid) samples. I also have a (non-random) "sample" from that distribution that is given and skews heavily towards the lower end of it. I would now ...
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1answer
67 views

Why and how to match variables using logistic regression?

I have a dataset of ~4.7K records focused on binary classification with 60 features. class 1 is of 1554 records and class 2 is ...
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222 views

Kernel Matching

I wish to estimate a treatment effect using Kernel Matching, but I'm confused about the process. From a high level, Is A or B correct? Or are both considered Kernel matching? A (1) Estimate ...
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Regression with two sample groups

I hope you can help me with the following problem: I have two sample groups. From the first group I know the explanatory variable x (pre-status) and from the second group I know the variable y (post-...
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1answer
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How to compare different causal inference methodologies for estimating Average Treatment Effect when true treatment effect is unknown?

I'm comparing various methods for estimating average treatment effects (ATEs) for cost savings in a case-control study on health insurance episode of care data for my employer. My company currently ...
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verifying pre-treatment trend assumption when there are multiple treatment time in Diff-in-Diff

One of my colleagues and I had a debate on Propensity Score Matching (PSM) + Diff-in-Diff (DD) when there are multiple time periods (some people called it staggered DD). Compared to the standard DD ...
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Match Adjusted Indirect Comparison with continuous and categorical variables [closed]

I am attempting to replicate the analysis here: http://nicedsu.org.uk/technical-support-documents/population-adjusted-indirect-comparisons-maic-and-stc/ (see appendix D). Specifically, the MAIC in ...
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1answer
137 views

How is a linear regression performed on exact matched data following $k:1$ matching?

I understand how regression is performed following exact matching on subclassification categories of data (for example, grouping individuals according to sex, age, etc.). Is regression on $k:1$ ...
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Multi feature matching

this might be a really intro question, But if I have two dataframes like: ...
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Setting the number of matches in Genetic Matching

I am using the GenMatch function from the Matching R-package to achieve a balance between the covariates in a treatment and control group. The GenMatch function allows to set M, which is according ...
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1answer
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Is it possible of overfit using Propensity score matching with the MatchIt R package?

I have a very large patient cohort and I am trying to define cases and controls whilst minimizing selection bias. Further down the line, I am using Cox regression to assess the efficacy of particular ...
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Separate Matching Analyses for Heterogenous ATT Effects

I have three treatments, and I'm trying to calculate the ATTs. The literature in my field seems to deal with this one of two ways. The first way involves conducting separate matching procedures for ...

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