| 000 | 01827nam a2200337| 4500 | ||
|---|---|---|---|
| 001 | 84024 | ||
| 005 | 20220104152845.0 | ||
| 010 |
_a978-3-319-18536-1 _dcompra |
||
| 090 | _a84024 | ||
| 100 | _a20190128d2015 k||y0pory50 ba | ||
| 101 | 0 | _aeng | |
| 102 | _aUS | ||
| 200 | 1 |
_aInnovative statistical methods for public health data _bDocumento electrn̤ico _fedited by Ding-Geng (Din) Chen, Jeffrey Wilson |
|
| 210 |
_aCham _cSpringer International Publishing _d2015 |
||
| 215 |
_aXIV, 351 p. _c45 il. |
||
| 225 | 2 | _aICSA book series in statistics | |
| 300 | _aColocaȯ̂: Online | ||
| 303 | _aThe book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference, and it can be used in graduate level classes. | ||
| 410 | 1 | _x2199-0980 | |
| 606 |
_93627 _aEstats̕tica |
||
| 606 |
_94386 _aSad͠e pb͠lica |
||
| 606 |
_928641 _aMedicina _xInvestigaȯ̂ |
||
| 680 | _aQA276 | ||
| 702 |
_933935 _aChen _bDing-Geng _4340 |
||
| 702 |
_964199 _aWilson _bJeffrey _4340 |
||
| 801 | 0 |
_gRPC _aPT |
|
| 856 | _uhttps://doi.org/10.1007/978-3-319-18536-1 | ||
| 942 |
_2lcc _cF _n0 |
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