000 | 03732cam a2200337Ii 4500 | ||
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001 | 9781315151526 | ||
008 | 180706t20182018fluad ob 001 0 eng d | ||
020 |
_a9781315151526 _q(e-book : PDF) |
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020 |
_a9781351638043 _q(e-book: Mobi) |
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020 |
_a9781498740777 _q(e-book) |
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020 |
_z9781498740760 _q(hardback) |
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024 | 7 |
_a10.1201/9781315151526 _2doi |
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035 | _a(OCoLC)1005688197 | ||
040 |
_aFlBoTFG _cFlBoTFG _erda |
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050 | 4 |
_aRC337 _b.G87 2018 |
|
082 | 0 | 4 |
_a616.8900727 _bG927 |
100 | 1 |
_aGueorguieva, Ralitza, _eauthor. |
|
245 | 1 | 0 |
_aStatistical methods in psychiatry and related fields : _blongitudinal, clustered, and other repeated measures data / _cby Ralitza Gueorguieva. |
264 | 1 |
_aBoca Raton, Florida : _bCRC Press, _c[2018] |
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264 | 4 | _c©2018 | |
300 | _a1 online resource (xviii, 352 pages) | ||
336 |
_atext _2rdacontent |
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337 |
_acomputer _2rdamedia |
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338 |
_aonline resource _2rdacarrier |
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505 | 0 | 0 |
_tchapter Introduction / _r Gueorguieva Ralitza -- _tchapter Traditional Methods for Analysis of Longitudinal and Clustered Data / _r Gueorguieva Ralitza -- _tchapter Linear Mixed Models for Longitudinal and Clustered Data / _r Gueorguieva Ralitza -- _tchapter Linear Models for Non-Normal Outcomes / _r Gueorguieva Ralitza -- _tchapter Non-Parametric Methods for the Analysis of Repeatedly Measured Data / _r Gueorguieva Ralitza -- _tchapter Post Hoc Analysis and Adjustments for Multiple Comparisons / _r Gueorguieva Ralitza -- _tchapter Handling of Missing Data and Dropout in Longitudinal Studies / _r Gueorguieva Ralitza -- _tchapter Controlling for Covariates in Studies with Repeated Measures / _r Gueorguieva Ralitza -- _tchapter Assessment of Moderator and Mediator Effects / _r Gueorguieva Ralitza -- _tchapter Mixture Models for Trajectory Analyses / _r Gueorguieva Ralitza -- _tchapter Study Design and Sample Size Calculations / _r Gueorguieva Ralitza -- _tchapter Summary and Further Readings / _r Gueorguieva Ralitza. |
520 | _a"Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data. "--Provided by publisher. | ||
650 | 0 |
_aPsychiatry _xResearch _xStatistical methods. |
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776 | 0 | 8 |
_iPrint version: _z9781498740760 _w(DLC) 2017029497 |
856 | 4 | 0 |
_uhttps://www.taylorfrancis.com/books/9781315151526 _zClick here to view. |
942 |
_2lcc _cEBK |
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999 |
_c17980 _d17980 |