000			01965nam a2200289Ia 4500
003			OSt
005			20250923152038.0
008			220909b |||||||| |||| 00| 0 eng d
020			_a9781597180788
037			_cTextual
040			_aCSL _beng _cCSL
041			_aeng.
084			_aB28 Q0 _qCSL
100			_aGould, William _eauthor. _9846334
245		0	_aMaximum Likelihood Estimation with Stata
250			_a4t ed.
260			_aTexas : _bStata Press, _c2010.
300			_axi, 352p.
500			_aIncludes References 343-346p.; Author Index 347-348p.; Subject Index 349-352p.
520			_aMaximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
650			_aMaximum likelihood estimation. _9846335
650			_aStatistics. _9846336
700			_aPitblado, Jeffrey _eco-author. _9846337
700			_aPoi, Brian _eco-author. _9846338
942			_hB28 Q0 _cTEXL _2CC _n0
999			_c16274 _d16274