Results 241 to 250 of about 12,232,356 (294)

Modeling determinants of women's decision-making autonomy on agriculture and household matters in rural Ethiopia: a mixed effects beta regression tree analysis. [PDF]

PLoS One
Dadi TK, Tamiru D, Wondafrash B, Gebremariam MK.   +3 more
europepmc   +1 more source

Identification of modifiable gait parameters predictive of simulated tibial stress-fracture risk in men and women. [PDF]

Front Physiol
Nagaraja S, Rubio JE, Subramaniyan M, Tong J, Baggaley M, Edwards WB, Reifman J.   +6 more
europepmc   +1 more source

Lifestyle factors and symptom burden in endometriosis: an exploratory mixed-methods analysis of nutrition, physical activity, and psychosocial well-being. [PDF]

BMC Womens Health
Wulfhorst L, Henze A, Portius D.
europepmc   +1 more source

Climate and Edaphic Factors Partly Explain Leaf Litterfall Rates of Species From Tropical Semi-Deciduous Ecosystems. [PDF]

Ecol Evol
Ali AA, Magar AT.
europepmc   +1 more source

Preoperative frailty and tumor volume as determinants of primary management strategy and outcomes in petroclival meningioma patients. [PDF]

Front Surg
Kashlan R, Faraj R, Duggireddy H, Zohdy YM, Hasa A, Agudelo Arrieta M, Barrero Ruiz E, Assi J, Rodas A, Salmeron-Moreno K, Maldonado J, Tariciotti L, Pradilla G, Garzon-Muvdi T.   +13 more
europepmc   +1 more source

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Linear mixed function‐on‐function regression models

Biometrics, 2014
SummaryWe develop a linear mixed regression model where both the response and the predictor are functions. Model parameters are estimated by maximizing the log likelihood via the ECME algorithm. The estimated variance parameters or covariance matrices are shown to be positive or positive definite at each iteration.
exaly   +4 more sources

Bayesian composite quantile regression for linear mixed-effects models

Communications in Statistics - Theory and Methods, 2017
ABSTRACTLongitudinal data are commonly modeled with the normal mixed-effects models. Most modeling methods are based on traditional mean regression, which results in non robust estimation when suffering extreme values or outliers. Median regression is also not a best choice to estimation especially for non normal errors.
Maozai Tian, Heng Lian
exaly   +2 more sources

Lasso regression in sparse linear model with $$\varphi $$-mixing errors

Metrika, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peng, Ling, Zhu, Yan, Zhong, Wenxuan
openaire   +2 more sources