Questions tagged [tobit-regression]
Tobit regression is used to estimate a linear regression model when the dependent variable is censored, i.e. when it is only observed over an interval of its support.
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Possible censored data and Tobit regression
I want to study the impact of highways on deforestation. I am using annual data on forest cover. I define my deforestation/forest loss variable as a change in forest cover and if the change is zero or ...
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How to interpret the coefficients in robust weighted Tobit regression model?
I am looking for any reference helping explaining the coefficients in Tobit model for beginner. I found a topic in our exchange but it seems still not clear to me.
I am finding a handy reference like ...
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What statistical test compare truncated distribution
I have been taking measures of two populations of mice. One population runs for 10minutes and the other can barely run for 2-3 minutes. The problem is that I have too many mice to keep testing them ...
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Analysing a small data set with lots of zeros? Dependent variable is (semi?) continuous, one fixed (categorical) factor
Hoping to get some advice for choosing an appropriate model for my data. I have a small data set looking at the level of a particular protein (heat shock protein 70) in individuals exposed to ...
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Is using a tobit regression appropriate for structured missing data?
I have a data set with a significant amount of missing data and that missing data is not random.
I decided to change these NA values to 999 and apply a Tobit with right censoring after a cut-off point ...
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Random effects tobit if random effects are non-normal distributed
I have the following (panel tobit) data-generating process:
$y_{i, t}^* = a + bx_{i,t} + u_{i} + e_{i,t}$
$y_{i,t} = y_{i, t}^*$ if $y_{i, t}^* \geq 0$ and $y_{i,t} = 0$ otherwise.
where $i = 1,..., N;...
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Two part model - using the output of first as feature to second?
I am working on a two-part model to predict a continuous target variable $Y$, given a feature set $F$. $Y$ is product of two continuous variables - $A$ and $B$, where $A \epsilon [0, 1]$ and $B \...
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How to compute marginal effects E(y| y>0) of a tobit model in R?
I'm searching a way to compute the marginal effect E(y| y>0) in R. I'm using the package censReg that gives the tobit model and the marginal effect E(y) and nothing more.
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How to do LASSO regression with a dependent variable that has two limits
I would like to estimate a LASSO regression for a dependent variable that has a lower limit at -0.661 and an upper limit at 1 in R. I have already estimated a tobit regression without LASSO with the ...
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Tobit panel data or panel data with trunced dependent varibel
Does anyone know if it is possible to use the Tobit model and the data panels model together, especially in the R language?
I tried the censReg package, but it didn't address the inherent testing of ...
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Estimating Right Censored Data
I'm a newbie at Math, and I am just getting my feet wet when it comes to understanding math and statistics so please forgive my ignorance or question if it's already been answered or if materials are ...
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Prediction of a variable that lies within the interval $[0,1]$ with masses at the ends
I have a data set on kilometers travelled by households and the associated means of transport and now want to predict a means of transport's share in households' total kilometres travelled based on ...
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Manual Tobit Clustered Covariance Matrix Estimation (vcovCL package R)
Dear Stack Exchange users,
I estimated the following general (pooled) Tobit model using R:
$y_{i,t}^{*} = a + x_{i,t} \beta +\varepsilon_{i,t}, \hspace{1cm} t = 1, ..., T$
where
$y_{i,t} = y^{*}_{i,t}$...
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Prediction in Tobit II Model vs. Probit x Linear Model
I am estimating a Tobit Type II model with a binary selection (1/0) variable and a continuous outcome variable (0 to infinity, if selection = 1). I then would like to predict the conditional ...
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How to write a random effect in tobit models in R using the censReg package?
To analyse right-censored data, I'm using the tobit regression package called censReg in R.
When assuming a fixed effect model, this works fine.
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likelihood function of tobit model when y can only be 0 or 1
As you can see, , here is the likelihood function of tobit model when observed y equals 0 when it is smaller then $y_L$.
What is the form when observed y equals 0 when it is smaller then $y_L$, AND y ...
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Baseline adjustment when both pre- and post values are subject to left-censoring
Assume $X$ is a binary treatment variable, $Y$ is a continuous variable measured pre- and post-treatment $(Y_{pre}$, $Y_{post})$, and $Z$ represents the remaining covariates. Both $Y_{pre}$ and $Y_{...
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Zero Hidden layers + ReLu-Activation + Gradient Descent = Tobit?
when I train a neural network with zero hidden neurons and ReLu activation functions using gradient descent, can it be expected that the resulting weights are approximatly equal to those of a tobit ...
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Should I perform Tobit/Ordinal Regression instead of OLS?
I'm using regression to understand what demographic variables explain playtime and performance in an educational video game. Demographic variables are age is numerical while gender, race, income, ...
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Calculating the effect of trustworthiness on obtaining bank loan and on loan rate (interpretation question)
I am reading a paper that discusses how people's perception of borrower's trustworthiness affects his/her probability of loan approval, and also loan rate.
This is from a RFS paper on page 2474 (2.1) (...
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What type of model(s) can I use for my (definitely not linear) dependent variable?
I have dependent variable, measured with a range of 0-100% (nevertheless it takes on fairly few variables). It reflects the amount of sales reported for some purpose. The distribution looks as in the ...
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Do I have a censored variable or not? What is the mean of my data?
I have a variable variable from a survey, which has a range from never (0) to always (100) in 10 steps (0 -100). It is obviously a discrete (ordinal) variable, but I want to try to treat is as ...
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Wikipedia's likelihood function of tobit model
This is the likelihood of the tobit model on Wikipedia. To my understanding, the first is the normal density when y is greater than the threshold and the second is the cdf of y for everything below ...
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Tobit Regression
I have a data set of Arsenic (As) in rice grain which is dependent of As in soil and also As in irrigation water. The permissible limit of As in rice grain is 400 ppb however in reality more than that ...
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Manual calculation - instrumental variable with a tobit distribution in the 2nd stage, different results with robust errors
Cross Posted at Stack Exchange.
I am trying to correct my standard errors, when using an ols distribution in the first stage and using a tobit distribution in the second. For some reason, I am getting ...
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Predicted values well outside of the censored range
I am working with an endogenous independent survey variable, $x$, which has a value range from 0 - 10, where 0 is always and 10 is never. Because the question pertains to wrongdoing, the answer to the ...
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2SLS or IV with a tobit distribution in the first stage
I would like to use a two stage least squares approach (2SLS), where the first stage would benefit from a Tobit specification.
I cross posted this on stackoverflow because there might be quite some ...
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Is it practical to use Tobit models predictively for censored latent variables?
I'm developing a model in R estimating vehicle miles traveled (VMT) using Tobit specification, since my data include a cluster of zero VMT values.
I understand that the coefficients given by a Tobit ...
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best regression model for a percentage of function variable
I am trying to choose the best regression model for a dependent variable 'percentage of normal shoulder function'. This variable is non normal and clustered at the high end of the possible range, ie ...
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Tobit model for continuous zero inflated data?
I would like advice on how to apply an appropriate linear model to my data.
I have several continuous independent variables, and a dependant variable with continuous distance measurements.
This ...
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Asking: interpret tobit regression to estimate willingness to pay from payment card
I have a research question, that I have to evaluate the Willingness to pay data for conservation. My input data in the type of payment card : $0, <\$2, \$2-\$4, \dotsc, >\$10$. I use middle ...
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Predictive Margins After Mixed-Effect Tobit
I'm hoping to get advice on the difference between two predictive margins outputs after running a mixed-effect tobit regression (in Stata 16.0).
Here is a sample output (modified from my actual case),...
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2-stage selection model with censoring: Heckman selection model with second stage censoring
I am seeking to get some insights on the application of two-part Tobit-type models to a distribution with potentially selection (from 0 into +ve) and upper truncation (censoring of data at 100%).
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A workaround for using linear models (rather than Tobit) with censored data?
I have a left censored dependent variable where many of the observations have a value of zero. The data is clustered (multiple measurements over time for each person). I initially decided to use a ...
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Estimation of censored regression model
I am refreshing my knowledge with respect to econometric modelling in general.
I came across page 201 of the book 'Enjoyable Econometrics by Philip Franses' and I had some difficulties interpreting ...
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Multiple regression for left-censored independent and dependent variables
I am interested in developing a predictive multiple regression model which predicts a concentration of one compound based on the measured concentrations of several other compounds. Both the dependent ...
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Unbiased estimation of regression coefficients conditional on a range of the dependent variable
I am interested in the relationship between a set of explanatory variables and a particular outcome variable for values of the outcome above a certain cutoff. Can I simply regress the outcome on the ...
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Conditional heteroscedasticity for the tobit model in Layman's terms
I have been using the crch package for modelling censored data with the tobit model. I noticed early on that the errors (by far) are not normally distributed by ...
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Question about deriving probabilities in the Tobit model
In the Tobit model: Why do you divide by σ when deriving the probability that y = 0? Is it something to do with the assumption that ε is distributed N(0,σ^2) and not N(0,1)? If this is the case why ...
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What is really the Scale or Sigma parameter of a tobit regression?
In this most upvoted CV answer on that topic the "scale" parameter (aka "sigma" in Stata) thrown in a tobit regression output is explained to be "the estimated standard ...
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Hurdle model vs left censored model
When dealing with response variables that have lots and lots of zeros, is there a clear argument for when hurdle models are preferred and when left censored or tobit models are preferred?
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Picking from Logistic vs Survival Model
I have a health data set for measuring the effectiveness of a drug. (Age, Gender(0,1), Morbidity(1,2,3), Dosage(0,1), Group (a,b), Effect (Not effective =0, effective = 1), and Time (days needed for ...
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How to get rid of zero standard error values, missing t-values and p-values
I was running a couple of Tobit regressions on SAS. Surprisingly, I found that estimates from one model show 0 standard errors, missing (.) t-values and p-values. Why did this happen? What does this ...
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Comparing the output and fit of an OLS and a Tobit model, and comparing Tobit models
I am trying to estimate a quite complicated model (many variables with different structures), with a limited dependent variable, which ranges from 0-100% with about 45% of the sample having an ...
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Censored Regression/Tobit: coefficients decrease drastically when non-normal distribution is assumed
I am trying to use a Tobit/ censored regression model to estimate the effect of a certain political condition on a tax. Our dependent variable is zero-inflated because in most of our observations this ...
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My Tobit model gives all infinite standard deviations
I am trying to do a Tobit estimation (in R) because my dependent variable ranges from 0-100 with many values at a 100.
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standard error estimate in CRCH
[Disclosure: I previously posted this over at stackoverflow, but I think that was the wrong place as I got no response. I've since deleted that post.]
I need to run a regression on censored data, and ...
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Censored regression with right censored data
I'm kind of new to Stats and R in general and I'm looking to clear some doubts. I'm trying to use Censored regression models to do the analysis of my qPCR data. The response variable is continuous (Ct ...
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Tobit model: Left and right censoring
In my data, my outcome variable days.to.event is conceptually left censored at 0 days and right censored at 30 days. However, since the ...
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Tobit model with flexible censoring point in R
I am currently writing my MSc thesis and I am using a Tobit model.
My data consists of fleet and sales data. The censored dependent variable is quantity and this quantity is higher than the fleet ...
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