###### Estimation

- third, the empirical methodology used in this analysis corrects a major shortcoming in the existing literature by using a censored dependent variable in estimation. (thefreedictionary.com)
- Tobit analysis, which explicitly accounts for a censored dependent variable , eliminates this source of estimation bias. (thefreedictionary.com)
- Estimation issues pertaining to regression with censored dependent variables are also presented. (thefreedictionary.com)
- Part I begins with an excellent introduction to Stata and follows with general treatments of the estimation, testing, fitting, and interpretation of models for categorical dependent variables. (stata.com)
- Economists have known for many years that lagged dependent variables can cause major estimation problems, but researchers in other disciplines are often unaware of these issues. (statisticalhorizons.com)
- Hence, if μ i {\displaystyle \mu _{i}} is believed to be correlated with one of the dependent variables, an alternative estimation technique must be used. (wikipedia.org)

###### categorical

- Regression Models for Categorical Dependent Variables Using Stata, Third Edition , by J. Scott Long and Jeremy Freese, is an essential reference for those who use Stata to fit and interpret regression models for categorical data. (stata.com)
- The authors also discuss how many improvements made to Stata in recent years-factor variables, marginal effects with margins , plotting predictions using marginsplot -facilitate analysis of categorical data. (stata.com)
- These studies are typically analyzed by treating cumulative exposure as a categorical variable and then comparing disease or mortality rates between different exposure groups. (sfu.ca)
- In this project, an extension to the Cox proportional hazards model is used to treat cumulative exposure as a continuous variable and model the dose-response curve nonparametrically for a study of aluminium smelter workers conducted by the British Columbia Cancer Agency and compare the results to the categorical analyses. (sfu.ca)
- Modeling Discrete Choice: Categorical Dependent Variables, L. (virginia.edu)
- In statistics, logistic regression, or logit regression, or logit model is a regression model where the dependent variable (DV) is categorical. (wikipedia.org)

###### Logistic Regression

- It draws the analogy between modeling discrete choice and building a regression model with a dummy dependent variable and on an example illustrates the need for estimating the probability of a choice rather than the choice itself, which leads to a special kind of regression - logistic regression. (virginia.edu)
- Cases where the dependent variable has more than two outcome categories may be analysed in multinomial logistic regression, or, if the multiple categories are ordered, in ordinal logistic regression. (wikipedia.org)
- The reason for using logistic regression for this problem is that the values of the dependent variable, pass and fail, while represented by "1" and "0", are not cardinal numbers. (wikipedia.org)
- Ordinal logistic regression deals with dependent variables that are ordered. (wikipedia.org)
- Binary logistic regression is used to predict the odds of being a case based on the values of the independent variables (predictors). (wikipedia.org)

###### binary-dependent variable

- In this article, we present a technique and critical test statistic for assessing the fit of a binary-dependent variable model (e.g., a logit or probit). (cambridge.org)
- This article covers the case of a binary dependent variable-that is, where the output can take only two values, "0" and "1", which represent outcomes such as pass/fail, win/lose, alive/dead or healthy/sick. (wikipedia.org)

###### discrete

- This volume presents detailed discussions of regression models that are appropriate for a variety of discrete dependent variables. (worldcat.org)
- Simultaneous Equations Models with Discrete and Censored Dependent Variables ," Chapter 9. (thefreedictionary.com)
- A Thurstonian model is a latent variable model for describing the mapping of some continuous scale onto discrete, possibly ordered categories of response. (wikipedia.org)

###### latent variable

- In Type I Tobit, the latent variable absorb both the process of participation and 'outcome' of interest. (wikipedia.org)
- Type IV introduces a third observed dependent variable and a third latent variable. (wikipedia.org)
- In the model, each of these categories of response corresponds to a latent variable whose value is drawn from a normal distribution, independently of the other response variables and with constant variance. (wikipedia.org)

###### predictor variables

- If Yi are independent observations with corresponding values xi of the predictor variables, then θ can be estimated by maximum likelihood. (wikipedia.org)

###### Stata

- The xtset command tells Stata that this is a "cross-section time-series" data set with identification numbers for persons stored in the variable id and a time variable t that ranges from 1 to 7. (statisticalhorizons.com)
- For a discussion of how to implement IV methods for lagged dependent variables in Stata, see pp. 274-278 in Rabe-Hesketh and Skrondal (2012). (statisticalhorizons.com)

###### compute

- 12 ] developed a numerical method to compute the linear elastic static and dynamic response of structures with epistemic uncertainty represented by evidence variables, which integrated the moment concept and finite element method and also suited to -boxes variables. (hindawi.com)
- If you are adventuresome, you can also compute the predicted value of the dependent variable from your regression analysis and plot it against the observed value using scattergram . (janda.org)

###### predictors

- The xtreg command fits a random-intercepts model by default, with lwage as the dependent variable and the subsequent four variables as predictors. (statisticalhorizons.com)

###### model

- The model is one of a censored dependent variable because observations at the limits are observed. (thefreedictionary.com)
- This analysis reproduces the predicted cell frequencies for Bartlett's data using a log-linear model of no three-variable interaction (Bishop, Fienberg, and Holland 1975, p. 89). (sas.com)
- The analysis of variance table shows that the model fits since the likelihood ratio test for the three-variable interaction is nonsignificant. (sas.com)
- But including a lagged dependent variable in a mixed model usually leads to severe bias. (statisticalhorizons.com)
- Are you calling this polynomial because you logged variables or did you transform via higher powers (squared, cubedd, etc.) some variables, if so, described how model variables were transformed and why. (talkstats.com)
- However, for finite vectors of random variables there is a close approximation to the i.i.d model. (wikipedia.org)
- Dummy variables are "proxy" variables or numeric stand-ins for qualitative facts in a regression model. (wikipedia.org)
- (wikipedia.org)

###### instrumental

- Economists have developed a variety of methods for solving the problem, most of them relying on some form of instrumental variable (IV) analysis. (statisticalhorizons.com)
- Instrumental variables or GMM techniques are commonly used in this situation, such as the Arellano-Bond estimator. (wikipedia.org)

###### dummy

- Dummy variables are used as devices to sort data into mutually exclusive categories (such as smoker/non-smoker, etc. (wikipedia.org)
- For example, in econometric time series analysis, dummy variables may be used to indicate the occurrence of wars or major strikes. (wikipedia.org)
- A dummy variable can thus be thought of as a truth value represented as a numerical value 0 or 1 (as is sometimes done in computer programming). (wikipedia.org)
- Then the intercept (the value of the dependent variable if all other explanatory variables hypothetically took on the value zero) would be the constant term for non-members but would be the constant term plus the coefficient of the membership dummy in the case of group members. (wikipedia.org)
- Dummy variables are used frequently in time series analysis with regime switching, seasonal analysis and qualitative data applications. (wikipedia.org)
- Dummy variables may be incorporated in traditional regression methods or newly developed modeling paradigms. (wikipedia.org)
- Note that the coefficients attached to the dummy variables are called differential intercept coefficients. (wikipedia.org)

###### constant variance

- It is typically assumed to be normally distributed with a mean of 0, constant variance, and independent of the other variables on the right-hand side . (statisticalhorizons.com)

###### coefficients

- The violation of this assumption can bias both the coefficient for the lagged dependent variable (usually too large) and the coefficients for other variables (usually too small). (statisticalhorizons.com)
- When the dependent variable is logged and the coefficients are small, multiplying them by 100 gives approximate percentage changes in the dependent variable. (statisticalhorizons.com)

###### populations

- A cross-sectional study is a type of observational research that analyzes and compares populations without manipulating variables within the study environm. (reference.com)

###### variation

- Therefore, it is important to know (and report) the pattern of variation in your chosen dependent variable. (janda.org)
- The independent variables represent inputs or causes, i.e., potential reasons for variation or, in the experimental setting, the variable controlled by the experimenter. (wikipedia.org)

###### multiple independent variables

- Multiple linear regression is a very common technique that uses one dependent variable and multiple independent variables. (talkstats.com)
- It is possible to have multiple independent variables and/or multiple dependent variables. (wikipedia.org)

###### data

- The independent variables are the data collected in the survey. (wikipedia.org)
- An example is a data set containing forecasts of one or multiple macroeconomic variables produced by multiple individuals (the first dimension), in multiple series (the second dimension) at multiple times periods (the third dimension) and for multiple horizons (the fourth dimension). (wikipedia.org)
- Another way to structure panel data would be the wide format where one row represents one observational unit for all points in time (for the example, the wide format would have only two (left example) or three (right example) rows of data with additional columns for each time-varying variable (income, age). (wikipedia.org)

###### Levels

- As in the text, the variable levels are simply labeled 1 and 2. (sas.com)
- Blocking: A schedule for conducting treatment combinations in an experimental study such that any effects on the experimental results due to a known change in raw materials, operators, machines, etc., become concentrated in the levels of the blocking variable. (wikipedia.org)

###### known

- Dependent variables also known as responses are the important measurable food quality indices. (expertsmind.com)

###### effect

- According to the University of New Mexico, a causal study examines a cause and effect between variables. (reference.com)
- Independent variables are the parameters such as ingredients and processing condition which have effect on product quality. (expertsmind.com)
- The random intercept u i represents the combined effect on y of all unobserved variables that do not change over time. (statisticalhorizons.com)
- Sometimes, independent variables may be included for other reasons, such as for their potential confounding effect, without a wish to test their effect directly. (wikipedia.org)
- If there was a concern that the machine traffic might have an effect on the variable being measured (e.g. death of strawberry plants), then a control treatment would receive the machine traffic but no herbicide. (wikipedia.org)

###### Error

- This exercise proved to me that many different variable was influencing my error. (talkstats.com)
- Can you tell us about the variable used for printer 'ineffectiveness' AKA error? (talkstats.com)
- To be more precise, I should have said 'positional error' instead of error which are three dimensional (X, Y, Z). You mix in that another couple factor and I got over 10 dependants variables. (talkstats.com)
- But since I'm planning to attack each one of those individually, I decided to talk about only one 1 dependant variable as general 'Error' in my question. (talkstats.com)