## Regression Analysis of Count DataStudents in both the natural and social sciences often seek regression models to explain the frequency of events, such as visits to a doctor, auto accidents or job hiring. This analysis provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors combine theory and practice to make sophisticated methods of analysis accessible to practitioners working with widely different types of data and software. The treatment will be useful to researchers in areas such as applied statistics, econometrics, operations research, actuarial studies, demography, biostatistics, and quantitatively-oriented sociology and political science. The book may be used as a reference work on count models or by students seeking an authoritative overview. The analysis is complemented by template programs available on the Internet through the authors' homepages. |

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### Contents

IV | 1 |

V | 3 |

VI | 8 |

VII | 10 |

VIII | 15 |

IX | 17 |

X | 19 |

XI | 20 |

LXI | 226 |

LXII | 234 |

LXIII | 238 |

LXIV | 240 |

LXV | 242 |

LXVI | 244 |

LXVII | 245 |

LXVIII | 246 |

XII | 22 |

XIII | 27 |

XIV | 37 |

XV | 44 |

XVI | 50 |

XVII | 57 |

XIX | 59 |

XX | 61 |

XXI | 70 |

XXII | 77 |

XXIII | 79 |

XXIV | 85 |

XXV | 88 |

XXVI | 93 |

XXVII | 94 |

XXVIII | 95 |

XXIX | 96 |

XXX | 97 |

XXXI | 106 |

XXXII | 112 |

XXXIII | 117 |

XXXIV | 121 |

XXXV | 123 |

XXXVI | 128 |

XXXVII | 134 |

XXXVIII | 135 |

XXXIX | 136 |

XL | 137 |

XLI | 139 |

XLII | 140 |

XLIII | 151 |

XLIV | 158 |

XLV | 163 |

XLVI | 168 |

XLVII | 182 |

XLVIII | 185 |

XLIX | 187 |

L | 188 |

LI | 189 |

LII | 190 |

LIII | 192 |

LIV | 207 |

LV | 216 |

LVI | 218 |

LVII | 219 |

LVIII | 220 |

LIX | 221 |

LX | 222 |

LXIX | 250 |

LXXI | 251 |

LXXII | 252 |

LXXIII | 256 |

LXXIV | 260 |

LXXV | 263 |

LXXVI | 269 |

LXXVII | 272 |

LXXVIII | 273 |

LXXIX | 275 |

LXXX | 276 |

LXXXI | 280 |

LXXXII | 287 |

LXXXIII | 290 |

LXXXIV | 293 |

LXXXV | 294 |

LXXXVI | 299 |

LXXXVII | 300 |

LXXXIX | 301 |

XC | 302 |

XCI | 307 |

XCII | 309 |

XCIII | 313 |

XCIV | 323 |

XCV | 324 |

XCVI | 325 |

XCVII | 326 |

XCVIII | 331 |

XCIX | 336 |

C | 343 |

CI | 344 |

CII | 345 |

CIII | 350 |

CIV | 356 |

CV | 358 |

CVI | 364 |

CVII | 367 |

CIX | 369 |

CX | 371 |

CXI | 374 |

CXII | 375 |

CXIII | 376 |

CXIV | 378 |

379 | |

399 | |

404 | |

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### Common terms and phrases

alternative analysis application approach assumed assumption asymptotically bivariate bootstrap Cameron and Trivedi Chapter CM test coefficients component conditional mean function conditional variance consider consistent estimator correctly specified count models covariates defined denote dependent variable deviance doctor visits econometrics effects model example exponential family exponential mean finite mixture first-order conditions fixed effects frequency functional form gamma Gurmu Hausman heteroskedasticity hurdle model individual lagged leads likelihood function linear model linear regression log-likelihood log-likelihood function logit marginal distributions maximum likelihood estimation measurement errors methods misspecification moment-based moments multivariate NB2 model nonlinear normal null hypothesis number of events observations obtained overdispersion parameters Poisson distribution Poisson model Poisson PMLE Poisson regression polynomial Pr[y probability random effects random effects model random variable regressors residuals restricted sample serial correlation series expansion standard errors term test statistic truncated underdispersion unobserved heterogeneity variance function variance matrix vector zero

### References to this book

Univariate Discrete Distributions Norman L. Johnson,Adrienne W. Kemp,Samuel Kotz Limited preview - 2005 |

Multivariate Statistical Modelling Based on Generalized Linear Models Ludwig Fahrmeir,Gerhard Tutz No preview available - 2001 |