logit


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lo·git

(lō'git),
The logarithm of the ratio of frequencies of two different categoric and mutually exclusive outcomes such as healthy and sick.
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Logit Model for the Presence of Osteomuscular Problems in Workers of the Healthcare Sector
In order to analyze the data obtained, a multinomial logit model was employed.
Different models were developed in the literature including univariate analysis (Beaver, 1966), multiple discriminated analysis (MDA) model (Altman, 1968), logit model (Ohlson, 1980), probit model (Zmijewski, 1984), hazard model (Shumway, 2001), and neural network model (Charitou, Neophytou, & Charalambous, 2004), etc.
Previous research in joint mode-and-complexity choice has centered on single nested logit models and mixed logit models that address correlation only in unobservables among options that share the same level of trip complexity.
Epidemiologists and clinical researchers often estimate logit models and report odds ratios.
This is achieved by developing latent class logit (LC) and random parameters logit (RPL) models to identify how the human-related factors influence injury severity of crashes.
"the dividend payout model", which was presented by the binary logit model and "the dividend level change model", which in turn was shown in the form of the multinominal logit model.
This study compares the performance of longstanding methodological techniques of multinomial logit and ordinal probit models with more recent methods of decision tree and artificial neural network models, and combines individual models into ensembles to test if the amalgamation of the multiple methodologies enhances the classification accuracy of crash injury severity outcomes.
Those factors found to have a significant dummy coefficient are used in developing a logistic regression (logit) model to formulate filter rules for share selection and subsequent portfolio construction.
This assessment was accomplished by applying a multivariate unbalanced logit model, utilising all 14 MIP headline indicators, using time horizons ranging from one to three years before crisis, which was represented by periods with output gap lower than negative 2 per cent.
The Binomial Logit technique was used to predict the magnitude of influence of the various factors associated with migration from rural to urban localities.