Conditional Logit modelConditional Logit model is part of:
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Data and results shared seamlessly
Data and results shared seamlessly One of the greatest advantages of XLSTAT is the way you can share data and results seamlessly. As the results are stored in Microsoft Excel, anyone can access them. There is no need for the receiver to have an XLSTAT license or any additional viewer which makes your team-work easier and more affordable. In addition, results are easily integrable into other Microsoft Office software such as PowerPoint, so that you can create striking presentation in minutes.
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Accessible - Available in many languages
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Automatable and customizable
Automatable and customizable Most of the statistical functions available in XLSTAT can be called directly from the Visual Basic window of Microsoft Excel. They can be modified and integrated to more code to fit to the specificity of your domain. Adding tables and plots as well as modifying existing outputs becomes easy. Furthermore, XLSTAT includes some special tools on the dialog boxes to generate automatically the VBA code in order to reproduce your analysis using the VBA editor or to simply load pre-set settings. This effortless automation of routine analysis will be a huge time saver on your part.
Principle of conditional Logit model
The conditional logit model is based on a model similar to that of the logistic regression. The difference is that all individuals are subjected to different situations before expressing their choice (modeled using a binary variable which is the dependent variable). The fact that the same individuals are used in taken in account by the conditional logit model .
(NB: the observations are not independent within a block corresponding to same individual).
The conditional logit model is a method mostly used in conjoint analysis, it is nevertheless useful when analyzing a certain type of data. It is McFadden (1973) who introduced this model.
Instead of having one line per individual like in the classical logit model, there will be one row for each category of the variable of interest. If one seeks to study transportations, for example, there will be four types of transports (car / train / plane / bike), each type of transport have characteristics (their price, their environmental costs...) but an individual can choose only one of four transportations. As part of a conditional logit model, all four options are presented to each individual and the individual choose his preferred option. We have for N individuals, N * 4 rows with 4 rows for each individual associated with each transportation. The binary response variable will indicate the choice of the individual (1) and 0 if the individual did not choose this option.
In XLSTAT-Conjoint analytical software, you will also have to select a column associated with the name of the individuals (with 4 lines per individual in our example). The explanatory variables will also have N * 4 lines.
Conditional Logit model method
The conditional logit model is based on a model similar to that of the logistic regression except that instead of having individual characteristics, there will be characteristics of the different alternatives proposed to the individuals.
The probability that individual i chooses product j is given by:
Pij = eβTzij / ΣkeβTzik
From this probability, we calculate a likelihood function: l(β) = Σi=1..nΣj=1..J yij log(Pij)
With y being a binary variable indicating the choice of individual i for product j and J being the number of choices available to each individual.
To estimate the model parameters β (the coefficients of the linear function), it seeks to maximize the likelihood function. Unlike linear regression, an exact analytical solution does not exist. It is therefore necessary to use an iterative algorithm. XLSTAT-Conjoint uses a Newton-Raphson algorithm.