TY - BOOK ID - 1625677 TI - Regression models for categorical dependent variables using stata. AU - Freese, Jeremy AU - Long, J. Scott PY - 2006 SN - 1597180114 9781597180115 PB - Texas Stata Corporation DB - UniCat KW - Programming KW - Quantitative methods in social research KW - Mathematical statistics KW - Regression Analysis KW - Social sciences KW - Statistical methods KW - Data processing KW - Stata KW - Regression analysis. KW - Data processing. KW - #SBIB:303H4 KW - 519.246 KW - 301.085 KW - 311 KW - 681.333 KW - 681.33 KW - Regression analysis KW - -519.536 KW - Behavioral sciences KW - Human sciences KW - Sciences, Social KW - Social science KW - Social studies KW - Civilization KW - Analysis, Regression KW - Linear regression KW - Regression modeling KW - Multivariate analysis KW - Structural equation modeling KW - 519.246 Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression KW - Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression KW - Informatica in de sociale wetenschappen KW - Kwantitatieve sociologische onderzoeksmethoden KW - Statistiekwetenschap KW - Softwarepakket KW - Programmering KW - -Data processing KW - Stata. KW - 519.536 KW - Statistical methods&delete& KW - Social sciences - Statistical methods - Data processing UR - https://www.unicat.be/uniCat?func=search&query=sysid:1625677 AB - "The goal of Regression Models for Categorical Dependent Variables Using Stata, Third Edition is to make it easier to carry out the computations necessary to fully interpret regression models for categorical outcomes by using Stata's margins command. Because the models are nonlinear, they are more complex to interpret. Most software packages that fit these models do not provide options that make it simple to compute the quantities useful for interpretation. In this book, the authors briefly describe the statistical issues involved in interpretation, and then they show how you can use Stata to perform these computations."--Back cover. ER -