Results 241 to 250 of about 312,787 (305)

Assessing three altruism facets by economic games and self-report: a multitrait-multimethod investigation. [PDF]

Sci Rep
Binder L, Schultze M, Chen FS, Windmann S.   +3 more
europepmc   +1 more source

PFAS endocrine disruption affecting pubertal development: exposure-response is steeper below median PFAS serum concentrations. [PDF]

Environ Health
van Larebeke N, Voorspoels S, Den Hond E, Leermakers M, Schoeters G.   +4 more
europepmc   +1 more source

Open-Set Recognition of Human Activities from Head-Mounted Inertial Sensor. [PDF]

Sensors (Basel)
Cortese A, Solbiati S, Scandelli A, Giudici A, Antonello N, Trojaniello D, Boracchi G, Caiani EG.   +7 more
europepmc   +1 more source

Policy Levers for First-Contact Healthcare Provider Choice: A Discrete Choice Experiment in Shanghai's Hierarchical Medical System. [PDF]

Appl Health Econ Health Policy
Gong Y.
europepmc   +1 more source

Avian malaria and invasion success: Contrasting infection patterns in two introduced Eurasian sparrows in North America (<i>Passer domesticus</i> and <i>Passer montanus</i>). [PDF]

Int J Parasitol Parasites Wildl
Trigueros AC, Robertson BQ, Parker PG.
europepmc   +1 more source

Clinically significant prostate cancer detection with deep learning in a multi-center magnetic resonance imaging study. [PDF]

Sci Rep
Alzate-Grisales JA, Mora-Rubio A, Perán-Teruel M, Beltrán AN, Torres CR, García JMO, García-García F, Tabares-Soto R, García-Gómez JM, de la Iglesia-Vayá M.   +9 more
europepmc   +1 more source

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Interpreting logit models

The Stata Journal: Promoting communications on statistics and Stata, 2022
The parameters of logit models are typically difficult to interpret, and the applied literature is replete with interpretive and computational mistakes. In this article, I review a menu of options to interpret the results of logistic regressions correctly and effectively using Stata.
openaire   +1 more source

Pooling Logit Models

Journal of Marketing Research, 1986
The typical testing for equality of parameters across several response functions cannot be performed when the dependent variable is a probability. The authors investigate the pooling issues of the response function when the model is specified as a transformational logit.
Hubert Gatignon, David J. Reibstein
openaire   +1 more source

Ordered Logit Model

2014
The ordered logit model is a regression model for an ordinal response variable. The model is based on the cumulative probabilities of the response variable: in particular, the logit of each cumulative probability is assumed to be a linear function of the covariates with regression coefficients constant across response categories.
Grilli, Leonardo, Rampichini, Carla
openaire   +2 more sources