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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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Is it correct to use paired t test after 1:2 matching?

Is it correct to use paired t test after 1:2 propensity score matching? How we can do this in R? I found the following link in SPSS (https://www.researchgate.net/post/how_is_paired_t-...
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Compute Sensitivity and Specificity with Incomplete Data

I have two data sets $A$ and $B$ which I want to combine using statistical methods (e.g. some matching algorithms such as Nearest Neighbor). I have a third data set $C$ that encompasses the true ...
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R- Trouble understanding what loss function is being used by Genmatch (genetic matching) algorithm

I am having some trouble understanding what loss function is being minimized to ensure that we are converging towards the best set of weights in the Genmatch function in R. I was reading the paper on ...
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Matched case control data

I'm new to working with matched case-control data. I have a study where case individuals are matched to controls in a 1:3 way. This means that for every case (diseased) I have three matched controls (...
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R- trouble understanding how setting estimand to “ATE” is affecting matching in “Matching” package

I am working on a project where I am using observational data from patients and trying to find a causal relationship on how Treatment dose affects Patient recovery. Since the data is observational, I ...
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“Matching” groups in a clinical study

I have the following question regarding a clinical study in the Surgery department of an hospital: 1) I have two groups of patients: group A - comprising patients operated in 2016; group B - ...
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How to do PSM with panel data using PanelMatch?

I would greatly appreciate if you could let me know how to use PanelMatch for my dataset. Unfortunately, I couldn't find it's manual so I don't know how to find which firms are matched, how to extract ...
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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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How to understand “controls” in matching versus regression

I'm trying to understand matching in comparison to regression, especially how using 'controls' in regression changes in matching. The part I don't understand is about the distribution of covariates ...
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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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Matching on pre-treatment outcome in diff-in-diff

The parallel trends assumption for a difference-in-differences analysis does not require the level of the trends to be similar (just parallel). However, in a case where we want the levels to be ...
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Diff-in-diff with mactched control group

I want to run a diff-in-diff model. To choose an appropriate control group, I use a nearest-neighbor matching model based on several determinants of the outcome variable that I study. I was ...
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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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Variable ratio matching

I am working on a simulated study where I have variable number of control matches for my treatment subjects. I am new to this type of analysis. I realize after matching I can utilize logistic ...
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Conditional logistic regression on matched data with replacement

I'm using 1 to 5 matching on my data with replacement, where each treatment is paired to at most 5 control units with the possibility of one control unit being assigned to more than one treatment. ...
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compare single value to a sample

I wish to compare a single case (i.e. 100% of a population of 1) to a sample of another population. I am accustomed to using standardized differences for both dichotomous and continuous variables ...
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How does the “BiasAdjust” term in Match() function from Matching R package work?

In the Match() function in the Matching R package, it takes in inputs like: ...
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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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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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What is the purpose of using MatchIt in R with nearest neighbors for estimation of ATE if it does not report which pairs are matched?

I am currently using the matchit function in MatchIt in R. For example, in the call: ...
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91 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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271 views

3:1 matching with MatchIt in R. The number of matched control is not equal to 3 times the number of cases

Hello I'm using the MatchIt package in R I have a total of unmatched 116 treated cases and 462 unmatcehd non-treated case with the command ...
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Accounting for “surgeon preference” when modeling a binary surgical outcome

I'm trying to model the risk of a binary event following surgery (event=admitted for observation, y/n), and my main predictor is a three-level 'treatment' administered during the procedure (Tx_A, Tx_B,...
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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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Evaluating Impact of Unobserved Confounders - Is the E-Value applicable for Non-Significant Group Differences?

I have conducted an analysis of treatment effects based on observational data (via statistical matching). As suggested by VanderWeele and Ding (2017), I want to evaluate the sensitivity of my analysis ...
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Local Combinational Variable Vs. Hidden Markov Model based sequence matching

I am having trouble understanding the concept of Local Combinational Variable (LCV) as described in this paper at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2761287/ I do understand somewhat how an ...
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Matching: is here an equivalent for caliper with mahalanobis model (as in logit model)

I'm trying to set the caliper value to a matching with mahalanobis metric method in R. Although a smaller value effectively improves the model (and decreases the number of matched items as a tradeoff) ...
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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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31 views

Interacting treatment variables with independent variables in matched samples

Can we interact the treatment variables with independent control variables that have been used for matching? I have a binary treatment variable called 'medicine'. It indicates whether a person ...
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Modeling hip fracture incidence (hospital-based cohort design)

Hoping someone can help me out with a question I have on an analysis looking at prosthetic hip fracture incidence following hip replacement surgery (exposure=type of implant, with reference being the ...
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103 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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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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How to handle bias due to self-selection in one group

I want to compare two or three social groups across a set of dependent variables, using data from a longitudinal survey. The problem is that membership in one of the groups leads to a self-selection ...
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22 views

Appropriate statistical test after matching pairs

I am working on a project where I have twitter user profiles and their tweets. The users are divided based on their number of followers in two groups (g1 and ...
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48 views

How do I 'control for' between cases and controls in survival analysis?

I would appreciate some advice concerning the best practice for controlling covariates in KM curve survival analysis. Individuals suffer from headaches and individuals and are sub-grouped by ...
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Matching inflation

I have data on a few millions of patients, about 1000 of them are cases, that is, they were diagnosed having a certain disease at some timepoint in their life. I think I basically have two options: 1)...
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result of matching analysis in confounding case

currently I'm studying Observation Analysis in my college. One of the part study explain about matching analysis in confounding case. In here, they told me that when we doing matched analysis, ...
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Matching by or adjusting for confounders?

When using regression models with a binary exposure, how do you choose whether to adjust for a confounders as covariates or to match the two exposure groups according to the confounders and then ...
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Entropy matching or any other exact matching with DID

I am applying DID using diff in stata on a data set. However, I believe that few time variant variables may also be confounding variables and I want to control for them. Hence I would like to combine ...
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McNemar or Fisher exact test for propensity score matched data?

I want to analyze some propensity score matched data. In the literature McNemar test is usually used, since the data is "paired". However matching is not pairing in the common sense. Would it be ...
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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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Unsupervised solution to name matching problem python

I am working on a name matching problem. Some of the name challenges that we have to cover are: phonetic Spelling Variations e.g. Cairns vs Kearns or Smith vs Smyth Transliteration Spelling ...
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Web Content Partial matching algorithm suggestions?

I am trying to find a word or set of words or a similar word in the new web page scraped from publicly available sources to answer a question. I have a small list of keywords against which I would ...
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207 views

“Matching” with cross-sectional studies: are the samples dependent?

I am comparing the prevalence of disease in participants of two separate cross-sectional surveys. One survey is from a group of prisoners and the other is from the general population. To account for ...
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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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Matching 3 Groups on multiple variables?

I'm doing an undergraduate psychological experiment on memory. We have 3 independent groups(between-participants), and we have 6 significant matching variables (e.g. gender, GPA.. etc.). 1) what is ...
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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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Match a path to a roadmap

I do not know if I'm in the right place but let us go. I got a relative path of an object. Which mean I know the distance and the direction between all the points of the path but do not know their GPS ...