000			01385nam a2200169 a 4500
005			20260901030415.0
008			250101s2019 xx o 000 0 eng d
100	1		_aLiying Luo
245	1	0	_aConstraints in Random Effects Age-Period-Cohort Models
264		1	_barXiv _c2019
336			_atext
338			_aonline resource
520			_aRandom effects (RE) models have been widely used to study the contextual effects of structures such as neighborhood or school. The RE approach has recently been applied to age-period-cohort (APC) models that are unidentified because the predictors are exactly linearly dependent. However, it has not been fully understood how the RE specification identifies these otherwise unidentified APC models. We address this challenge by first making explicit that RE-APC models have greater -- not less -- rank deficiency than the traditional fixed-effects model, followed by two empirical examples. We then provide intuition and a mathematical proof to explain that for APC models with one RE, treating one effect as an RE is equivalent to constraining the estimates of that effect's linear component and the random intercept to be zero. For APC models with two RE's, the effective constraints implied by the
506	0		_aOpen access — freely available to read.
856	4	0	_uhttps://arxiv.org/pdf/1904.07672v1 _yRead the full paper (PDF)
942			_cERES
999			_c714 _d714