000 | 02466cam a2200301 i 4500 | ||
---|---|---|---|
001 | 18078514 | ||
003 | ISI Library, Kolkata | ||
005 | 20250312020024.0 | ||
008 | 140324s2014 flu b 001 0 eng | ||
010 | _a 2013047327 | ||
020 | _a9781466517158 | ||
040 |
_aISI Library _bEnglish |
||
082 | 0 | 4 |
_223rd _a005.753 _bAr735 |
245 | 1 | 0 |
_aAnalyzing spatial models of choice and judgment with R/ _cDavid A. Armstrong II et. al. |
260 |
_aBoca Raton: _bCRC Press, _c2014 |
||
300 |
_axx, 336 pages; _bdig; _c24 cm. |
||
490 | 0 | _aStatistics in the Social and Behavioral Sciences Series | |
504 | _aIncludes bibliography and index | ||
505 | 0 | _aIntroduction -- The Basics -- Analyzing Issue Scales -- Analyzing Similarities and Dissimilarities Data -- Unfolding Analysis of Rating Scale Data -- Unfolding Analysis of Binary Choice Data -- Advanced Topics. | |
520 | _aModern Methods for Evaluating Your Social Science Data With recent advances in computing power and the widespread availability of political choice data, such as legislative roll call and public opinion survey data, the empirical estimation of spatial models has never been easier or more popular. Analyzing Spatial Models of Choice and Judgment with R demonstrates how to estimate and interpret spatial models using a variety of methods with the popular, open-source programming language R. Requiring basic knowledge of R, the book enables researchers to apply the methods to their own data. Also suitable for expert methodologists, it presents the latest methods for modeling the distances between points―not the locations of the points themselves. This distinction has important implications for understanding scaling results, particularly how uncertainty spreads throughout the entire point configuration and how results are identified. In each chapter, the authors explain the basic theory behind the spatial model, then illustrate the estimation techniques and explore their historical development, and finally discuss the advantages and limitations of the methods. They also demonstrate step by step how to implement each method using R with actual datasets. The R code and datasets are available on the book’s website. | ||
650 | 4 | _aComputing | |
650 | 4 | _aProgramming | |
650 | 0 | _aSpatial analysis (Statistics) | |
650 | 4 | _aSpatial Behavior | |
650 | 4 | _aR (Computer Program Language) | |
700 | 1 |
_aArmstrong II, David A _eauthor |
|
942 |
_2ddc _cBK _01 |
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999 |
_c435880 _d435880 |