similar to: Using discrete choice data to estimate marginal willingness to pay (MWTP)

Hello, I am new to R and I am trying to estimate a discrete model with three choices. I am stuck at a point and cannot find a solution. I have probability functions for occurrence of these choices, and then I build the likelihood functions associated to these choices and finally I build the general log-likelihood function. There are four parameters in the model, three of them are associated to

Hello all, I'd like to announce the availability of a mailing list for a newly-formed SIG (Special Interest Group) dedicated to using R for Discrete Choice Modelling. This list is intended for discussion of issues revolving around the design and analysis of Discrete Choice (aka Stated Choice, Stated Preference or Choice-Based Conjoint) experiments. While R has good infrastructure for

Hi, I'm struggling trying to specify a multinomial logit discrete choice model in R. Any help and/or code examples appreciated. I am specifically interested in specifying a model where no universal choice set exists and each choice set has a variable number of alternatives (one of which is chosen) see data below. Many Thanks, David PS I have asked earlier but without reply. Is it

To all, Does anyone know whether there are any Discrete Choice Modeling modules for R?? Thanks, Charlie ------------------------- Charles H. Rosa, Ph.D. Staff Research Engineer General Motors Corporation R&D and Planning Mail Code 480-106-359 30500 Mound Rd Warren, MI 48090-9055 Tel/work/cell: +1 248 670-8389 Fax/work: +1 586 986-0574

Hello, I need a little initial help with the MNP package. I am trying to analyze a discrete choice experiment with the following settings: - choice sets consist of 3 alternatives - choice alternatives are constructed by e.g. two attributes, say brand and price. - brand has three levels and price has four levels - every respondent has to answer 4 different choice sets (drawn randomly or

Dear all: When I am trying to get the marginal effects: summary(result7,adv_inc_ratio=mean(m9201 $adv_inc_ratio),adv_price_ratio=mean(m9201$adv_price_ratio), ...(SOME MORE CONTINUOUS AND DISCRETE VARIABLES BUT I AM NOT LISTING)... regW=c (0,mean(m9201$regW),1), regWM=c(0,mean(m9201$regWM),1)) It gave out an error message: Error in summary.Design(result7, adv_inc_ratio = mean(m9201

We are in the process of analyzing data from a discrete-choice conjoint survey and are looking for a consultant who can help us assess willingness to pay (WTP). We are currently able to assess overall WTP using the coefficients from our conjoint analysis but would like assistance in determining if significant differences in WTP exist across a number of subgroups via a segmented analysis or some

Hi I am trying to estimate stated preferences for Tv sets by using mlogit. The choice set is designed as with 4 attributes: [ brand(has 4 levels), technology(has two levels), class[has 4 levels), price(has 4 levels)] There are 16 choice sets with 4 alternatives each one (i.e. each respondent has evaluated 64 cards in total). Therefore, there are 64 rows in the table below. The data in csv file

Dear all, I haven?t used R for panel data analysis so far, but now I am looking for a package respectively some starting point for binary choice panel data analysis in R. For starters most of my effects are individual and my dependent variable is just binary. Thanks for any suggestions in advance! best matt

Hi, I would like to fit Logit models for ordered data, such as those suggested by Greene (2003), p. 736. Does anyone suggests any package in R for that? By the way, my dependent variable is ordinal and my independent variables are ratio/intervalar. Thanks, Iuri. Greene, W. H. Econometric Analysis. Upper Saddle River, NJ: Prentice Hall, 2003

Dear R users, I would like to perform Latent Class Logit Models for the analysis of choice experiments in environmental valuation. This kind of analysis is usually performed with NLogit Software (http://www.limdep.com). I attach the results I usually obtain using NLogit and NLogit model specifications. For Random parameter models and Logit Models I usually perform my analysis with the package

I have 10000 bivarate samples (x1, x2), and I want to estimate the marginal density of x2. I searched the R manual but couldn't find a function that can do this job. It seems "density" only works for single-variate samples. Can anybody help me with it? Thanks a lot! Best, J. Deng

I have a question regarding calculating marginal effects (change in the probability due to a one unit change in x) for a probit or for that matter any discrete choice model. Does R have a function that will essentially do this: dE[y|x] ------- = f(x'beta)*beta dx Stata has a command called "mfx" that calculates the marginal effects at the mean (of the x

Dear All, A method for the estimation is univariate unimodal densities (with unknown mode) is described in "Statistical Inference under Order Restrictions" by Barlow et al.. Would anyone know whether there is an R-implementation (preferably with reference) for the estimation of univariate discrete unimodal densities (with unknown mode)? Thanks in advance for your help. Kind

Hi, I have a discrete choice model to estimate for a client that I originally planned to estimate as an aggregate model using a clogit routine. Now the client is asking for results for many segments of the respondents which would mean, if I stayed with my original plan, I would have to estimate a large number of models. I could certainly do this, but I'm thinking that it would be

Dear all, I have a continuous variable that can take on values between 0 and 100, for example: x<-runif(100,0,100) I also have a second variable that defines a series of thresholds, for example: y<-c(3, 4.5, 6, 8) I would like to convert my continuous variable into a discrete one using the threshold variables: If x is between 0 and 3 the discrete variable should be 1 If x is between 3

I want to investigate possible relationships between two discrete variables. I have tried a few things but figured you guys might be able to point me at some purpose built functions. Our scientists score results of tests which are performed in lets say, 8 positions. The scores are assigned a value of 1,2,3 or 4. I want to know if there is a correlation between the test results and the

Hello, I am using the mda package and in particular the fda routine to classify in term of gear a set of 20 trips. I preformed a flexible discriminant analysis (FDA) using a set of 151 trips. FDAT1 <- fda(as.factor(gear) ~ . , data =matrizR) A total of 22 predictors were considered. 20 of the predictors are "numeric" and 2 are "factors/discrete". The resulting FDA

Hi everyone, We have been trying to construct a Lasso-cox model with discrete time. We conducted follow-up examinations on the epileptic attack after tumor surgical resection among glioma patients. The patients are followed-up in the 6/12/24 months after surgical resection, which makes the epilepsy-free time discrete (6/12/24 months). We calcluated many features from the T2-images

Hello Everyone,   I have just started learning R and am in the process of figuring out what it can and can't do. I must say I am very impressed with R so far and am amazed that something this good can actually be free.   Recently, I finished reading R for SAS and SPSS Users and have begun reading SAS and R and Data Manipulation with R. Based on what I've read in these books and elsewhere,