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Method.bib
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@article{Gower1971,
langid = {english},
title = {A {{General Coefficient}} of {{Similarity}} and {{Some}} of {{Its Properties}}},
volume = {27},
issn = {0006341X},
doi = {10/dxtrt7},
abstract = {A general coefficient measuring the similarity between two sampling units is defined. The matrix of similarities between all pairs of sample units is shown to be positive semidefinite (except possibly when there are missing values). This is important for the multidimensional Euclidean representation of the sample and also establishes some inequalities amongst the similarities relating three individuals. The definition is extended to cope with a hierarchy of characters.},
number = {4},
journaltitle = {Biometrics},
date = {1971-12},
pages = {857-871},
author = {Gower, J. C.},
file = {/home/nalf/Zotero/storage/UAJN6S9E/Gower - 1971 - A General Coefficient of Similarity and Some of It.pdf}
}
@incollection{Kaufman1990,
langid = {english},
location = {{Hoboken, NJ, USA}},
title = {Partitioning {{Around Medoids}} ({{Program PAM}})},
isbn = {978-0-470-31680-1 978-0-471-87876-6},
url = {http://doi.wiley.com/10.1002/9780470316801.ch2},
booktitle = {Wiley {{Series}} in {{Probability}} and {{Statistics}}},
publisher = {{John Wiley \& Sons, Inc.}},
urldate = {2018-08-30},
date = {1990-03-08},
pages = {68-125},
editor = {Kaufman, Leonard and Rousseeuw, Peter J.},
file = {/home/nalf/Zotero/storage/UF2MJ2D9/Kaufman and Rousseeuw - 1990 - Partitioning Around Medoids (Program PAM).pdf},
doi = {10.1002/9780470316801.ch2},
note = {Short: 10/bwcxw5}
}
@article{Rousseeuw1987,
langid = {english},
title = {Silhouettes: {{A}} Graphical Aid to the Interpretation and Validation of Cluster Analysis},
volume = {20},
issn = {03770427},
doi = {10/fdxwqh},
shorttitle = {Silhouettes},
abstract = {A new graphical display is proposed for partitioning techniques. Each cluster is represented by a so-called silhouette, which is based on the comparison of its tightness and separation. This silhouette shows which objects he well within their cluster, and which ones are merely somewhere in between clusters. The entire clustering is displayed by combining the silhouettes into a single plot, allowing an appreciation of the relative quality of the clusters and an overview of the data configuration. The average silhouette width provides an evaluation of clustering validity, and might be used to select an ‘appropriate’ number of clusters.},
journaltitle = {Journal of Computational and Applied Mathematics},
date = {1987-11},
pages = {53-65},
author = {Rousseeuw, Peter J.},
file = {/home/nalf/Zotero/storage/KASMJNFF/Rousseeuw - 1987 - Silhouettes A graphical aid to the interpretation.pdf}
}
@article{Kruskal1952,
title = {Use of {{Ranks}} in {{One}}-{{Criterion Variance Analysis}}},
volume = {47},
issn = {0162-1459},
doi = {10/gfsnx8},
abstract = {Given C samples, with n i observations in the ith sample, a test of the hypothesis that the samples are from the same population may be made by ranking the observations from from 1 to Σn i (giving each observation in a group of ties the mean of the ranks tied for), finding the C sums of ranks, and computing a statistic H. Under the stated hypothesis, H is distributed approximately as χ2(C – 1), unless the samples are too small, in which case special approximations or exact tables are provided. One of the most important applications of the test is in detecting differences among the population means.* * Based in part on research supported by the Office of Naval Research at the Statistical Research Center, University of Chicago.},
number = {260},
journaltitle = {Journal of the American Statistical Association},
date = {1952-12-01},
pages = {583-621},
author = {Kruskal, William H. and Wallis, W. Allen},
file = {/home/nalf/Zotero/storage/JI3A5UUZ/Kruskal and Wallis - 1952 - Use of Ranks in One-Criterion Variance Analysis.pdf;/home/nalf/Zotero/storage/5MPPAM2M/01621459.1952.html}
}
@article{Mundform2011,
langid = {english},
title = {Number of {{Replications Required}} in {{Monte Carlo Simulation Studies}}: {{A Synthesis}} of {{Four Studies}}},
volume = {10},
issn = {1538-9472},
doi = {10/gfvvc2},
shorttitle = {Number of {{Replications Required}} in {{Monte Carlo Simulation Studies}}},
abstract = {Monte Carlo simulations are used extensively to study the performance of statistical tests and control charts. Researchers have used various numbers of replications, but rarely provide justification for their choice. Currently, no empirically-based recommendations regarding the required number of replications exist. Twenty-two studies were re-analyzed to determine empirically-based recommendations.},
number = {1},
journaltitle = {Journal of Modern Applied Statistical Methods},
date = {2011-05-01},
pages = {19-28},
author = {Mundform, Daniel J. and Schaffer, Jay and Kim, Myoung-Jin and Shaw, Dale and Thongteeraparp, Ampai and Supawan, Pornsin},
file = {/home/nalf/Zotero/storage/ND6X8DGB/Mundform et al. - 2011 - Number of Replications Required in Monte Carlo Sim.pdf}
}
@article{Pearson1900,
langid = {english},
title = {X. {{{\emph{On}}}}{\emph{ the Criterion That a given System of Deviations from the Probable in the Case of a Correlated System of Variables Is Such That It Can Be Reasonably Supposed to Have Arisen from Random Sampling}}},
volume = {50},
issn = {1941-5982, 1941-5990},
doi = {10/cpxzh4},
number = {302},
journaltitle = {The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science},
date = {1900-07},
pages = {157-175},
author = {Pearson, Karl},
file = {/home/nalf/Zotero/storage/GDU7X2NQ/Pearson - 1900 - X. iOn the criterion that a given system of devi.pdf}
}
@article{Hope1968,
eprinttype = {jstor},
eprint = {2984263},
langid = {english},
title = {A {{Simplified Monte Carlo Significance Test Procedure}}},
volume = {30},
doi = {10/gfvvc3},
abstract = {TheuseofMonteCarlotestprocedurefsorsignificantcestingw, ithsmaller referencseetsthanarenowgenerallyused,is advocated.It is shownthat, forgivenoX= l/n,n a positiveintegert,hepowerof the MonteCarlo test proceduries a monotoneincreasinfgunctionofthesizeofthereferencseet, thelimitofwhichisthepowerofthecorrespondinugniformlmyostpowerful test. The powerfunctionasnd efficiencoyf the MonteCarlo testto the uniformlmy ostpowerfutlestare discussedin detailforthecase wherethe testcriterionis N(y,1). The cases whenthe testcriterionis Student's t-statistainc dwhentheteststatistiicsexponentialdlyistributeadreconsidered also.},
number = {3},
journaltitle = {Journal of the Royal Statistical Society. Series B (Methodological)},
date = {1968},
pages = {582-598},
author = {Hope, Adery C. A.},
file = {/home/nalf/Zotero/storage/YPI4GRKR/Hope - 1968 - A Simplified Monte Carlo Significance Test Procedu.pdf}
}
@report{Conover1979,
langid = {english},
title = {On {{Multiple}}-{{Comparisons Procedures}}},
url = {https://www.osti.gov/biblio/6057803},
abstract = {The U.S. Department of Energy's Office of Scientific and Technical Information},
number = {LA-7677-MS},
institution = {{Los Alamos Scientific Lab., NM (USA)}},
urldate = {2019-02-23},
date = {1979-02-01},
author = {Conover, W. J. and Iman, R. L.},
file = {/home/nalf/Zotero/storage/XD2HG6QX/Conover and Iman - 1979 - Multiple-comparisons procedures. Informal report;/home/nalf/Zotero/storage/WFYAP4N3/6057803.html}
}
@article{Beasley1995,
langid = {english},
title = {Multiple {{Regression Approach}} to {{Analyzing Contingency Tables}}: {{Post Hoc}} and {{Planned Comparison Procedures}}},
volume = {64},
issn = {0022-0973, 1940-0683},
doi = {10/cd4djs},
shorttitle = {Multiple {{Regression Approach}} to {{Analyzing Contingency Tables}}},
abstract = {Post hoc and planned comparison procedures for interpreting chi square contingency-table test results, not currently discussed in most standard text books, are presented. A planned comparison procedure that simplifies the tedious process of partitioning a contingency table by creating single-degree-of-freedom con trasts through a regression-based approach is proposed. Importantly, these post hoc methods supplement the analysis of standardized residuals by reporting the per centage contribution for each cell to the overall chi-square statistic (relative contri bution) and to the percentage of variance shared by the two factors (absolute contri bution). Both methods can be readily incorporated into existing statistical packages such as SAS or SPSS. The equivalence of the percentage contribution method to the more common standardized residual method is also presented along with an exam ple of a typical application.},
number = {1},
journaltitle = {The Journal of Experimental Education},
date = {1995-10},
pages = {79-93},
author = {Beasley, T. Mark and Schumacker, Randall E.},
file = {/home/nalf/Zotero/storage/TZEKY2C5/Beasley and Schumacker - 1995 - Multiple Regression Approach to Analyzing Continge.pdf}
}
@article{Dunn1961,
title = {Multiple {{Comparisons}} among {{Means}}},
volume = {56},
issn = {0162-1459},
doi = {10/gd85vm},
abstract = {Methods for constructing simultaneous confidence intervals for all possible linear contrasts among several means of normally distributed variables have been given by Scheffé and Tukey. In this paper the possibility is considered of picking in advance a number (say m) of linear contrasts among k means, and then estimating these m linear contrasts by confidence intervals based on a Student t statistic, in such a way that the overall confidence level for the m intervals is greater than or equal to a preassigned value. It is found that for some values of k, and for m not too large, intervals obtained in this way are shorter than those using the F distribution or the Studentized range. When this is so, the experimenter may be willing to select the linear combinations in advance which he wishes to estimate in order to have m shorter intervals instead of an infinite number of longer intervals.},
number = {293},
journaltitle = {Journal of the American Statistical Association},
date = {1961-03-01},
pages = {52-64},
author = {Dunn, Olive Jean},
file = {/home/nalf/Zotero/storage/DCBZFDTJ/Dunn - 1961 - Multiple Comparisons among Means.pdf;/home/nalf/Zotero/storage/KR67Y532/01621459.1961.html}
}