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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14 views

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
27 views

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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31 views

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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31 views

match on a variable that itself depends on matching

I want to determine whether Program X improved graduation rates at a higher ed institution. Students self-select into this program, so I'm using propensity score matching (with the ...
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20 views

Is there a way to evaluate the accuracy or misclassification rate of the linear model that the R package MatchIt uses to build propensity scores? [closed]

m1.out <- matchit(Treatment ~ co_variate_1 + co_variate_2 + co_variate_3, data = mydata, method = "nearest", ratio = 1) summary(m1.out) I am ...
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51 views

Propensity Score Matching with Cox Regression

I am conducting a survival analysis with a Cox regression whereby the outcome variable (promotion to a senior role) is either 0 or 1. I am particulalry interested in the hazard rate (i.e., the 'hazard'...
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12 views

case-control matching with stratum of different length

I want to match cases with controls. My restriction is that a case must be assigned k controls. I use the notation $n:m$, being a stratum with $n$ cases and $m$ controls. For some cases I can ...
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17 views

Propensity score matching in r using panel data [closed]

I want to conduct PSM using firm panel data in r. matchit(treat ~ leverage + cash + roa + mtb + asset, data=data) This gave me a result of only very similar one ...
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1answer
23 views

Matching Before Randomization in R [closed]

I would like to divide 100 subjects into 50 matched pairs. Within each pair, I would like to randomize one subject into a treatment group and the other into a control group. I would like to match the ...
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1answer
50 views

advantages and disadvantages of IPTW vs propensity score matching?

what are the advantages and disadvantages of IPTW (Inverse Probability of Treatment Weighting) comparing to PSM (propensity score matching) in dealing with confounding variables?
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41 views

In an observational study where matching is properly conducted, should we expect the $ATE$ to be equal to the $ATT$?

In a randomized study, I know that the $ATE=ATT=ATC$, where $ATE$ is the average treatment effect, $ATT$ is the average treatment effect on the treated, and $ATC$ is the average treatment effect on ...
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1answer
71 views

Matching subjects with themselves when evaluating short term outcomes

I am considering a simple causal inference scenario; Let's say we want to examine the effect of paracetamol (treatment) on curing headache (outcome). When performing matching, is it okay to match ...
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9 views

Matching: strange p-value for Rosenbaum sensitivity test using rbounds package

I'm using R to conduct genetic matching (Matching package) and do Rosenbaum sensitivity tests to test the sensitivity of my ...
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2answers
29 views

Does rowwise distribution of random values in creating a normally distributed vector variable in matrix(rnorm(.), byrow=TRUE) damage normality?

(Reprodicible example added) 150-character-limitless full question is: Does the rowwise distribution of values in creating a normally distributed vector variable via ...
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2answers
54 views

What statistical test would I use to test that both data sources are matching [closed]

Suppose I am only working with two datasets, Data Source 1 with columns Customer ID and ...
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1answer
14 views

Is there a name for simple categorical matching / distance matching hybrid?

I have a cohort of individuals I need to match. I'm matching over age, gender, and location, but this isn't enough to get good results from just distance matching or propensity score matching. Is ...
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1answer
18 views

What does summary of the model (T-stat and p-values) after Matching using R's “Matching” package indicate?

I am using the GenMatch and Match functions in R's Matching package to balance covariates in an observational study via Genetic Matching. However, the documentation for this package does not describe ...
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1answer
29 views

How to data entry for a matched case control study

Please tell me how to enter my samples in excel can I first enter cases then controls in same sheet? What about match ID and group indicator?
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2answers
112 views

Exact matching + multiple regression on high-dimensional treatment-control study?

I'm working on a project with healthcare data where episodes of care in the treatment and control groups must be matched to estimate average treatment effect (ATE). I have several hundred covariates ...
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52 views

NcNemar's test for 1:2 matched data

Does anyone use McNemar's test for fractional values after 1-to-2 propensity score matching? How correct would it be? For instance, let me have 0-1 outcomes and the following matched observations (...
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2answers
146 views

Propensity scores in logistic regression models

I have a query after reading a paper, which is about the effectiveness of a medical device. In summary, what the authors did was 1. Generating a propensity score using a multivariable logistic ...
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1answer
28 views

Degrees of freedom in matching for calculating p-value of t-score

I am running a matching analysis using the Match function from the Matching R-package. My sample includes 86048 firms, from which 611 have received treatment. After matching on sector(exact), number ...
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13 views

Data matching technique

I have a database of different clients and I know from which countries these customers source their good from. E.g. XZY company sources 80% of the goods from China 10% from India and 10% from Russia. ...
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How to design inclusion criteria to match groups?

I am currently working on a study with a population of mostly veterans with chronic spinal cord injuries (goal n=60, currently n=27). We decided to add a comparison group of able-bodied controls that ...
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1answer
82 views

Propensity score matching with MatchIt: Question on missing standard mean differences in balance tab on cobalt package

I am using MatchIt to carry out some propensity score matching, and then using the cobalt package to generate the balance diagnostic. The summary() command on MatchIt has a known bug where it does not ...
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1answer
49 views

Why is Propensity Score called a distance measure as well?

I had to use Propensity score matching for my study. I used the MatchIt function in R and I studied what it actually does. I understand that the propensity score is calculated using Logistic ...
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In causal inference, is the usual unconfoundedness assumption interpreted to apply at the unit or covariate level?

Suppose for each unit $i \in \{1, \ldots, N\}$, we have that $(Y_i(1),Y_i(0))$ are the potential outcomes, $Z_i$ is the treatment, and $X_i$ the covariates. I have seen the following two ...
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If unconfoundedness holds under a set of covariates $X$, will it also hold on an extended set of covariates, $(X,X')$?

Suppose unconfoundedness holds for a set of potential outcomes $(Y(1),Y(0))$ and treatment $Z$, conditional on a set of covariates, $X$ such that: $$ (Y(1),Y(0)) \perp Z \mid X $$ Then, is it ...
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1answer
31 views

In Exact Matching in Causal Inference, why is it that that $P(X_i=x\mid Z_i = 1)= P(X_i=x\mid Z_i = 0)$ where $X,Z$ are the covariates and treatment?

In Exact Matching in Causal Inference, I read that because we assume exact matches, then exact balance occurs in the distribution of the covariates. It is then often stated that if $X,Z$ are the ...
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1answer
71 views

For Matching on a categorical variable with N categories, will it suffice to create (N-1) binary features and match on them?

I have data on patients who received different amounts of Occupational therapy (High Dose vs Low Dose) after a stroke. We are investigating if there are differences in recovery between patients from ...
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14 views

Estimating weights in the assignment problem

How would you learn a function with the emphasis on feature interactions? I have the standard assignment problem: $$ \max_{x_{ij}} \sum_{(i, j)} w_{ij} x_{ij}, $$ where $w_{ij}$ is the weight of ...
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1answer
87 views

How exactly to evaluate Treatment effect after Matching?

In Elizabeth's Stuart's 2010 paper "Matching methods for causal inference: A review and a look forward", she states the following: "Section 5: Analysis of the Outcome: ... After the matching has ...
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Best method to investigate treatment effect after creating a Matched control group using Gentic Matching (with replacement)?

Project background: I have data on patients who received varying amounts of therapy dose during treatment of stroke-induced paralysis. I wish to investigate if there are differences in motor-function ...
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1answer
249 views

Matching with Multiple Treatments

What's the best way to use matching methods with multiple treatment groups? I'm assessing the impact of an intervention on an outcome. For my first analysis, I used the MatchIt package (see code below)...
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1answer
69 views

is there a way to find suitable ratio for “ratio” in Matchit package in R

I am using matchit package in R to find a control set for my treated units and I am testing the model with different ratio to get suitable control set. Is there a way to find suitable ratio and I will ...
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2answers
28 views

Matching covariate selection- should we not match on binary features where overwhelming majority of subjects fall in one category?

I am trying to investigate if there is a relation between Occupational Therapy (OT) dosage for stroke patients and patient recovery. I have separated the patients into 2 groups by the amount of ...
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1answer
45 views

What type of regression for two groups of data?

I have data from 500 school children who took a test. 250 of the children have a certain type of disability (group A). Each child in group A was matched to a child on the basis of age, gender to a ...
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27 views

How to predict matching between two objects? [closed]

There is information from a website which connects questions from users to suitable professionals that might be interested in answering the particular questions. The data contains over 10.000 ...
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1answer
20 views

What distance function to use for matching observations on a mix of ordinal, nominal and numeric variables?

I'm trying to match potential respondents to a random sample from the target population, and not sure whether any of the usual methods available out-of-the-box in e.g. R are right for the job. ...
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1answer
114 views

Estimation of average treatment effect based on nearest neighbor matching [closed]

I would like to use R to duplicate the treatment effect estimation method used in Stata. Specifically, this is the Stata method I would like to duplicate. I have tried the package ...
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1answer
66 views

After performing Matching w/ replacement, should tests to evaluate treatment effect between the matched groups include repeated subjects?

I am using Genetic Matching to infer causality from observational data. Because I am matching with replacement, the matched Control group has multiple instances of some of the same subjects. In this ...
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46 views

Synthetic Controls vs Coarsened Exact Matching with weights vs Coarsened Exact Matching k2k

My question is mostly out of curiosity. How one should choose between synthetic controls and coarsened exact matching (CEM) when he/she wants to combine it with difference-in-difference design? ...
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1answer
46 views

In matching procedures in causal inference, will matching on more covariates always decrease the bias? Can the bias ever increase? [duplicate]

There are various matching procedures in the causal inference literature, from exact matching to propensity score matching and more. The goal is usually to find the Average Treatment Effect (ATE). ...
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22 views

Is matching necessary for prediction from logistic regression?

I have a data set with very imbalanced groups (about 3% have an effect, while 97% don't). I experimented with logistic regression and was convinced that I can get to a very good accuracy of prediction ...
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1answer
376 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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61 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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8 views

How to match different samples with different tests in a structural equations model? SPSS / AMOS

I am working on a study on hotels that analyzes the possible influence of the labor sastifacción (MSQ, 20 questions scale 1 to 5) in customer satisfaction (scale 1 to 5, questions that evaluate ...
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1answer
600 views

what's the difference between stratified sampling and matching?

I am trying to find a good technique to balance data in which the minority class is about 1% of the data. As I understood, the most common practice is matching. What is the difference, though, ...
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83 views

SMOTE algorithm gives better AUC than matching

I have a highly imbalanced data set: a total of 13000 patients, 160 having condition A, and various other features which could be predictors. In order to balance the data I did two things: 1) ...
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31 views

Difference in means test for coefficients from two matching models

I have a model estimating the effect of a treatment on two different populations, and a theoretical hypothesis that the effect should be larger for population A than for population B. I can address ...