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_aHA29 _b.T28 2009 |
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_a519.5 _222 |
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_aTarling, Roger, _eauthor. _9268259 |
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| 245 | 1 | 0 |
_aStatistical modelling for social researchers : _bprinciples and practice / _cRoger Tarling. |
| 264 | 1 |
_aLondon ; _aNew York : _bRoutledge, _c2009. |
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| 300 |
_ax, 210 pages : _billustrations, plans ; _c26 cm. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_aunmediated _bn _2rdamedia |
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| 338 |
_avolume _bnc _2rdacarrier |
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| 490 | 1 | _aSocial research today | |
| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | 0 |
_g1. _tStatistical modelling: An overview -- _g2. _tResearch designs and data -- _g3. _tStatistical preliminaries -- _g4. _tMultiple regression for continuous response variables -- _g5. _tLogistic regression for binary response variables -- _g6. _tMultinomial logistic regression for multinomial response variables -- _g7. _tLoglinear models -- _g8. _tOrdinal logistic regression for ordered categorical response variables -- _g9. _tMultilevel modelling -- _g10. _tLatent variables and factor analysis -- _g11. _tCausal modelling: simultaneous equation models -- _g12. _tLongitudinal data analysis -- _g13. _tEvent history models -- _gAppendix 1. _tThe generalised linear model -- _gAppendix 2. _tHandling tabular data. |
| 520 | _a"This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-linear models, multilevel models, latent variable models (factor analysis), path analysis and simultaneous equation models and models for longitudinal data and event histories. An accompanying website hosts the datasets and further exercises in order that the reader may practice developing statistical models."--Publisher's website. | ||
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_aSocial sciences _xResearch _xStatistical methods. |
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_aSocial sciences _xStatistical methods. _9370520 |
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_aSocial research today (Routledge (Firm)). _9268124 |
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