MatchIt | MatchIt provides a simple and straightforward interface | Development Tools library

 by   kosukeimai R Version: 3.0-2 License: No License

kandi X-RAY | MatchIt Summary

kandi X-RAY | MatchIt Summary

MatchIt is a R library typically used in Utilities, Development Tools applications. MatchIt has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

MatchIt provides a simple and straightforward interface to various methods of matching for covariate balance in observational studies. Matching is one way to reduce confounding and model dependence when estimating treatment effects. Several matching methods are available, including nearest neighbor matching, optimal pair matching, optimal full matching, genetic matching, exact matching, coarsened exact matching, and subclassification, some of which rely on functions from other R packages. A variety of methods to estimate propensity scores for propensity score matching are included. Below is an example of the use of MatchIt to perform full matching and assess balance:. Printing the MatchIt object provides details of the kind of matching performed.
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              MatchIt has a low active ecosystem.
              It has 153 star(s) with 37 fork(s). There are 6 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 17 open issues and 83 have been closed. On average issues are closed in 92 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of MatchIt is 3.0-2

            kandi-Quality Quality

              MatchIt has no bugs reported.

            kandi-Security Security

              MatchIt has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              MatchIt does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              MatchIt releases are available to install and integrate.
              Installation instructions are not available. Examples and code snippets are available.

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            MatchIt Key Features

            No Key Features are available at this moment for MatchIt.

            MatchIt Examples and Code Snippets

            No Code Snippets are available at this moment for MatchIt.

            Community Discussions

            QUESTION

            MatchIt combined with lapply(): Error in eval(object$call$data, envir = env) : object 'x' not found
            Asked 2021-Jun-02 at 16:47

            So my situation is the following: I have a large dataframe which contains the data I should use in matching analyses. I should, however, match inside subgroups that are defined by certain areas. Because I didn't want to do that "manually" for each subgroup (there are too many), I came up with an approach that divides the initial dataframe into sub-dataframes containing information of each unique treated area and the control areas, and saves these dataframes into a list. After this, I performed matching on the dataframes in the list using matchit function from R's MatchIt package. Here a heavily simplified example of how the dataframe list looks like:

            ...

            ANSWER

            Answered 2021-Jun-02 at 16:47

            Please see this issue, which asks the same question, and the documentation for match.data(), which answers it (see the data argument).

            This is an inherent limitation of match.data(), but the solution is simple and documented: supply the original dataset to the data argument of match.data(), as so:

            Source https://stackoverflow.com/questions/67736778

            QUESTION

            Propensity score matching with multiple imputation
            Asked 2021-May-19 at 19:03

            I have a dataset with a couple of missing values and would need to run a propensity score matching using the variable 'y' as Treatment variable and x1, x2 and x3 as variables for adjustment. By using the following code with Matchit

            ...

            ANSWER

            Answered 2021-Jan-04 at 22:49

            You should use the MatchThem package, was was specifically designed for performing matching after multiple imputation. The matchthem() function calls matchit() and performs matching within each imputed dataset. You can then check balance in the imputed dataset using the cobalt package, which was designed to be compatible with MatchThem. Afterward, you can use the with() function in MatchThem to estimate the effect. Here's an example of this workflow:

            Source https://stackoverflow.com/questions/65561517

            QUESTION

            Get only the fully matched cases using Matchit in R using 1:5 ratio
            Asked 2021-Apr-20 at 06:48

            I have matched my two groups with 1:5 ratio and noticed that my two resulting groups do not have a 1:5 ratio, similar to this question posted here:

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

            I have performed a match like this:

            ...

            ANSWER

            Answered 2021-Apr-20 at 06:48

            Just to answer my own question: It seems like you can force a full 1:5 match by adding: method = "optimal" to the function. Read more here: https://cran.r-project.org/web/packages/MatchIt/vignettes/matching-methods.html#optimal-pair-matching-method-optimal

            This however will decrease the success of matching. Would anyone know a way of selecting only those 1:5 cases from the original output?

            EDIT: As Noah pointed out, the 1:5 match can be forced, but this will ignore the caliper. See the documentation here: https://rdrr.io/cran/MatchIt/man/method_optimal.html I thought it was a bit hidden, but you can see under the header "Arguments" it says: "The arguments replace, caliper, and m.order are ignored with a warning."

            Source https://stackoverflow.com/questions/67160808

            QUESTION

            How to do 10-nearest neighbour propensity score matching? I only seem to found 1-1 nearest neighbour matching online
            Asked 2021-Apr-05 at 18:03

            #1:1 nearest neighbour

            ...

            ANSWER

            Answered 2021-Apr-05 at 18:03

            Your second code block is correct if you set ratio = 10. I'm not sure where 4 comes from. Note that this will perform nearest neighbor matching without replacement, which means if there are not 10 control units for each treated unit, you will not be able to find matches for all treated units. To do nearest neighbor matching with replacement, set replace = TRUE.

            Source https://stackoverflow.com/questions/66954279

            QUESTION

            Change levels and labels using the `as_factor` R haven function for table1 output
            Asked 2021-Mar-25 at 23:14

            I am trying to create a descriptive statistics table using the table1 with p-values and data from an SAV file. I read in the file using read_sav from the haven package.

            ...

            ANSWER

            Answered 2021-Mar-25 at 23:14

            Convert the tibble data frame to a normal data frame, then you can use factor and your p-value script to produce your Table 1.

            Source https://stackoverflow.com/questions/66804401

            QUESTION

            Propensity Score Matching with panel data
            Asked 2021-Mar-11 at 01:49

            I am trying to use MatchIt to perform Propensity Score Matching (PSM) for my panel data. The data is panel data that contains multi-year observations from the same group of companies.

            The data is basically describing a list of bond data and the financial data of their issuers, also the bond terms such as issued date, coupon rate, maturity, and bond type of bonds issued by them. For instance:

            Firmnames Year ROA Bond_type AAPL US Equity 2015 0.3 0 AAPL US Equity 2015 0.3 1 AAPL US Equity 2016 0.3 0 AAPL US Equity 2017 0.3 0 C US Equity 2015 0.3 0 C US Equity 2016 0.3 0 C US Equity 2017 0.3 0

            ......

            I've already known how to match the observations by the criteria I want and I use exact = Year to make sure I match observations from the same year. The problem now I am facing is that the observations from the same companies will be matched together, this is not what I want. The code I used:

            matchit(Bond_type ~ Year + Amount_Issued + Cpn + Total_Assets_bf + AssetsEquityRatio_bf + Asset_Turnover_bf, data = rdata, method = "nearest", distance = "glm", exact = "Year")

            However, as you can see, in the second raw of my sample, there might be two observations in one year from the same companies due to the nature of my study (the company can issue bonds more than one time a year). The only difference between them is the Bond_type. Therefore, the MathcIt function will, of course, treat them as the best control and treatment group and match these two observations together since they have the same ROA and other matching factors in that year.

            I have two ways to solve this in my opinion:

            1. Remove the observations from the same year and company, however, removing the observations might lead to bias results and ruined the study.

            2. Preventing MatchIt function match the observations from the same company (or with the same Frimnames)

            The second approach will be better since it will not lead to bias, however, I don't know if I can do this in MatchIt function. Hope someone can give me some advice on this or maybe there's any better solution to this problem, please be so kind to share with me, thanks in advance!

            Note: If there's any further information or requirement I should provide, please just inform me. This is my first time raising the question here!

            ...

            ANSWER

            Answered 2021-Mar-11 at 01:49

            This is not possible with MatchIt at the moment (though it's an interesting idea and not hard to implement, so I may add it as a feature).

            In the optmatch package, which perfroms optimal pair and full matching, there is a constraint that can be added called "anti-exact matching", which sounds exactly like what you want. Units with the same value of the anti-exact matching variable will not be matched with each other. This can be implemented using optmatch::antiExactMatch().

            In the Matching package, which performs nearest neighbor and genetic matching, the restrict argument can be supplied to the matching function to restrict certain matches. You could manually create the restriction matrix by restricting all pairs of observations in the same company and then supply the matrix to Match().

            Source https://stackoverflow.com/questions/66526115

            QUESTION

            gvim Systemverilog syntax matching :is there way to match `ifdef `ifndef `else and `endif
            Asked 2021-Feb-13 at 14:32

            I have used standard SystemVerilog syntax packages but not able to match(with % move the cursor between) these strings. This is in the context of matchit function in Vim(https://www.vim.org/scripts/script.php?script_id=39). The problem seems to be with backtick.

            I tried:

            ...

            ANSWER

            Answered 2021-Feb-12 at 13:48

            I'm assuming you have a file that looks like this:

            Source https://stackoverflow.com/questions/66160327

            QUESTION

            Scala match recursive objects
            Asked 2021-Jan-27 at 18:53

            I am a newbie in Scala and I want to build a small recursive pattern matching with objects. I keep getting a No match in the following code:

            ...

            ANSWER

            Answered 2021-Jan-27 at 18:53

            Your pattern matching construction was not really correct, please find fixed one below:

            Source https://stackoverflow.com/questions/65924782

            QUESTION

            Flutter Navigator 2.0 Routing via the Navigator()
            Asked 2020-Dec-14 at 05:10

            I am currently trying to build a web app with the new Flutter web beta. The thing is to be able to have a history, handle the forward and back buttons in the browser and be able to handle user inputs into the URL the new Navigator 2.0 API is required (at least from what I understood).

            There are only a few resources available currently, based on which I am trying to build my Navigator. The resources I used:

            I managed to get the Back and forward button, as well as the history working. However I am struggling to be able to handle the page switches (in the Navigator()). In the example from John he manages the different sites in the 'page: ' array of the Navigator Widget (in the routeDelegater). It seemed strange to me but I tried it like this and it did not really work (Code further down).

            In the 'page: []' I first tried to have booleans that trigger (like the show404) but that wasn't very clean so my next try was to get the current page as follows (in the array):

            ...

            ANSWER

            Answered 2020-Dec-04 at 14:12

            I actually managed to solve it by adding another function that is called in my Navigator() in the RouteDelegator under pages[]:

            Source https://stackoverflow.com/questions/65142566

            QUESTION

            Pandas - Convert a list present as string to a list
            Asked 2020-Dec-11 at 12:13

            I have a pandas dataframe with a column that is essentially an array but represented as a string. This dataframe can be recreated by

            ...

            ANSWER

            Answered 2020-Dec-11 at 11:47

            Does this solve your question?
            TOTAL TIME: 1 to 2 seconds

            Here I'm using the JSON library to do the computation as it is written in C(DONT GET CONFUSED WITH JSON'S FULL FORM) so its computationally efficient and fast.

            Source https://stackoverflow.com/questions/65250487

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

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