R: QQ Summary Statistics

qqstats {Matching} | R Documentation

## QQ Summary Statistics

### Description

This function calculates a set of summary statistics for the QQ plot of two samples of data. The summaries are useful for determining if the two samples are from the same distribution. If `standardize==TRUE`, the empirical CDF is used instead of the empirical-QQ plot. The later retains the scale of the variable.

### Usage

    qqstats(x, y, standardize=TRUE, summary.func)

### Arguments

`x` | The first sample.
`y` | The second sample.
`standardize` | A logical flag for whether the statistics should be standardized by the empirical cumulative distribution functions of the two samples.
`summary.func` | A user provided function to summarize the difference between the two distributions. The function should expect a vector of the differences as an argument and return summary statistic. For example, the `quantile` function is a legal function to pass in.

### Value

`meandiff` | The mean difference between the QQ plots of the two samples.
`mediandiff` | The median difference between the QQ plots of the two samples.
`maxdiff` | The maximum difference between the QQ plots of the two samples.
`summarydiff` | If the user provides a `summary.func`, the user requested summary difference is returned.
`summary.func` | If the user provides a `summary.func`, the function is returned.

### Author(s)

Jasjeet S. Sekhon, UC Berkeley, sekhon@berkeley.edu, http://sekhon.berkeley.edu/.

### References

Sekhon, Jasjeet S. 2011. "Multivariate and Propensity Score Matching Software with Automated Balance Optimization.” Journal of Statistical Software 42(7): 1-52. doi: 10.18637/jss.v042.i07

Diamond, Alexis and Jasjeet S. Sekhon. Forthcoming. "Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies.” Review of Economics and Statistics. http://sekhon.berkeley.edu/papers/GenMatch.pdf

### See Also

Also see `ks.boot`, `balanceUV`, `Match`, `GenMatch`, `MatchBalance`, `GerberGreenImai`, `lalonde`

### Examples

    #
    # Replication of Dehejia and Wahba psid3 model
    #
    # Dehejia, Rajeev and Sadek Wahba. 1999.``Causal Effects in
    # Non-Experimental Studies: Re-Evaluating the Evaluation of Training
    # Programs.''Journal of the American Statistical Association 94 (448):
    # 1053-1062.
    #

    data(lalonde)

    #
    # Estimate the propensity model
    #
    glm1  <- glm(treat~age + I(age^2) + educ + I(educ^2) + black +
                 hisp + married + nodegr + re74  + I(re74^2) + re75 + I(re75^2) +
                 u74 + u75, family=binomial, data=lalonde)

    #
    #save data objects
    #
    X  <- glm1$fitted
    Y  <- lalonde$re78
    Tr  <- lalonde$treat

    #
    # one-to-one matching with replacement (the "M=1" option).
    # Estimating the treatment effect on the treated (the "estimand" option which defaults to 0).
    #
    rr  <- Match(Y=Y,Tr=Tr,X=X,M=1);
    summary(rr)

    #
    # Do we have balance on 1975 income after matching?
    #
    qqout  <- qqstats(lalonde$re75[rr$index.treated], lalonde$re75[rr$index.control])
    print(qqout)

[Package Matching version 4.10-2 Index]