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Topic: Logit

Related Topics

Logistic regression

Artificial neural network

Maximum likelihood

Data mining

A priori algorithm

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	LOGIT
		LOGIT is used to estimate a conditional and/or multinomial logit model.
		There are three types of logit model: those where the regressors are the same across all choices for each observations, i.e., they are characteristics of the chooser, those where the regressors are characteristics of the specific choice, and mixed models, which have regressors of both kinds.
		In the second case (conditional logit), the regressors change across the choices, and a single coefficient is estimated for each set of regressors.
	www.tspintl.com /products/tsphelp/logit.htm (0 words)

	PA 765: Logit, Probit, and Log-linear Models
		Logit and probit extend the log-linear model to allow a mixture of categorical and continuous independent variables to predict one or more categorical dependent variables.
		Where the logit transformation is the natural log of the odds ratio, the function used in probit is the inverse of the standard normal cumulative distribution function.
		Probit coefficients correspond to the b coefficients in regression or the logit coefficients in logit or logistic regression.
	www2.chass.ncsu.edu /garson/pa765/logit.htm (15607 words)

	Stata help for logit
		Several auxiliary commands that can be run after logit, probit, or logistic estimation are described in [R] logistic postestimation.
		A list of related estimation commands is given in logistic estimation commands.
		Macros e(cmd) logit e(cmdline) command as typed e(depvar) name of dependent variable e(wtype) weight type e(wexp) weight expression e(title) title in estimation output e(clustvar) name of cluster variable e(offset) offset e(chi2type) Wald or LR; type of model chi-squared test e(vce) vcetype specified in vce() e(vcetype) title used to label Std.
	www.stata.com /help.cgi?logit (0 words)

	Multivariate Analysis UCR Sociology 203A Logit and Probit Example
		The logit and probit regression models regress a function of the probability that a case falls in a certain category of Y, on a linear combination of X variables.
		The logit model is exactly that: the left hand side is the logit of Y, or the log of the odds that a case falls in one category on Y versus another.
		Logit and probit models use the method of maximum likelihood to fit functions of proportions of cases at each level of the X vector that have a score of "1" on the dependent variable.
	faculty.ucr.edu /~hanneman/soc203a/logit.html (2799 words)

	LOGIT
		Given this future, LOGIT will be there to provide historic vocal and media links with a period when
		THE LOGIT PROJECT is in the early stages of development and if there are those amongst you who see a better way,or would like to invest some time on the development, please get in touch and we can move forward
		The SUBSCRIBER will prepay for a slice of our memory per annum which can be altered as time passes during the year The year will run for the date of inscription which will be communicated to the subscriber along with his password.
	www.logit.fr (0 words)

	Logit Analysis for CBC
		Logit analysis is an iterative procedure to find the maximum likelihood solution for fitting a multinomial logit model to the data.
		After logit converges on a solution, the output is displayed in the results window, and you are given the option to save the run to the utility file.
		To see how logit output and analysis by counting choices output are similar, we use the same procedure to estimate the distribution of choices for four concepts differing only in brand, plus a "None" option.
	www.sawtoothsoftware.com /support/SSIWeb_Support/online_help/hid_smrt_logitanalysis.htm (3506 words)

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