Data analysis using stata
by
 
Kohler, Ulrich Dr. phil.

Title
Data analysis using stata

Author
Kohler, Ulrich Dr. phil.

ISBN
9781597181105

Personal Author
Kohler, Ulrich Dr. phil.

Edition
3rd ed.

Publication Information
College Station, Tex. : Stata Press, c2012.

Physical Description
xxvi, 497 p. : ill. ; 24 cm.

Contents
Machine generated contents note: 1.The first time -- 1.1.Starting Stata -- 1.2.Setting up your screen -- 1.3.Your first analysis -- 1.3.1.Inputting commands -- 1.3.2.Files and the working memory -- 1.3.3.Loading data -- 1.3.4.Variables and observations -- 1.3.5.Looking at data -- 1.3.6.Interrupting a command and repeating a command -- 1.3.7.The variable list -- 1.3.8.The in qualifier -- 1.3.9.Summary statistics -- 1.3.10.The if qualifier -- 1.3.11.Defining missing values -- 1.3.12.The by prefix -- 1.3.13.Command options -- 1.3.14.Frequency tables -- 1.3.15.Graphs -- 1.3.16.Getting help -- 1.3.17.Recoding variables -- 1.3.18.Variable labels and value labels -- 1.3.19.Linear regression -- 1.4.Do-files -- 1.5.Exiting Stata -- 1.6.Exercises -- 2.Working with do-files -- 2.1.From interactive work to working with a do-file -- 2.1.1.Alternative 1 -- 2.1.2.Alternative 2 -- 2.2.Designing do-files -- 2.2.1.Comments -- 2.2.2.Line breaks -- 2.2.3.Some crucial commands --
 
Contents note continued: 2.3.Organizing your work -- 2.4.Exercises -- 3.The grammar of Stata -- 3.1.The elements of Stata commands -- 3.1.1.Stata commands -- 3.1.2.The variable list -- List of variables: Required or optional -- Abbreviation rules -- Special listings -- 3.1.3.Options -- 3.1.4.The in qualifier -- 3.1.5.The if qualifier -- 3.1.6.Expressions -- Operators -- Functions -- 3.1.7.Lists of numbers -- 3.1.8.Using filenames -- 3.2.Repeating similar commands -- 3.2.1.The by prefix -- 3.2.2.The {breach loop -- The types of foreach lists -- Several commands within a foreach loop -- 3.2.3.The forvalues loop -- 3.3.Weights -- Frequency weights -- Analytic weights -- Sampling weights -- 3.4.Exercises -- 4.General comments on the statistical commands -- 4.1.Regular statistical commands -- 4.2.Estimation commands -- 4.3.Exercises -- 5.Creating and changing variables -- 5.1.The commands generate and replace -- 5.1.1.Variable names -- 5.1.2.Some examples -- 5.1.3.Useful functions --
 
Contents note continued: 5.1.4.Changing codes with by, _n, and _N -- 5.1.5.Subscripts -- 5.2.Specialized recoding commands -- 5.2.1.The recode command -- 5.2.2.The egen command -- 5.3.Recoding string variables -- 5.4.Recoding date and time -- 5.4.1.Dates -- 5.4.2.Time -- 5.5.Setting missing values -- 5.5.Labels -- 5.7.Storage types, or the ghost in the machine -- 5.8.Exercises -- 6.Creating and changing graphs -- 6.1.A primer on graph syntax -- 6.2.Graph types -- 6.2.1.Examples -- 6.2.2.Specialized graphs -- 6.3.Graph elements -- 6.3.1.Appearance of data -- Choice of marker -- Marker colors -- Marker size -- Lines -- 6.3.2.Graph and plot regions -- Graph size -- Plot region -- Sealing the axes -- 6.3.3.Information inside the plot region -- Reference lines -- Labeling inside the plot region -- 6.3.4.Information outside the plot region -- Labeling the axes -- Tick lines -- Axis titles -- The legend -- Graph titles -- 6.4.Multiple graphs -- 6.4.1.Overlaying many twoway graphs --
 
Contents note continued: 6.4.2.Option by() -- 6.4.3.Combining graphs -- 6.5.Saving and printing graphs -- 6.6.Exercises -- 7.Describing and comparing distributions -- 7.1.Categories: Few or many? -- 7.2.Variables with few categories -- 7.2.1.Tables -- Frequency tables -- More than one frequency table -- Comparing distributions -- Summary statistics -- More than one contingency table -- 7.2.2.Graphs -- Histograms -- Bar charts -- Pie charts -- Dot charts -- 7.3.Variables with many categories -- 7.3.1.Frequencies of grouped data -- Some remarks on grouping data -- Special techniques for grouping data -- 7.3.2.Describing data using statistics -- Important summary statistics -- The summarize command -- The tabstat command -- Comparing distributions using statistics -- 7.3.3.Graphs -- Box plots -- Histograms -- Kernel density estimation -- Quantile plot -- Comparing distributions with Q-Q plots -- 7.4.Exercises -- 8.Statistical inference --
 
Contents note continued: 8.1.Random samples and sampling distributions -- 8.1.1.Random numbers -- 8.1.2.Creating fictitious datasets -- 8.1.3.Drawing random samples -- 8.1.4.The sampling distribution -- 8.2.Descriptive inference -- 8.2.1.Standard errors for simple random samples -- 8.2.2.Standard errors for complex samples -- Typical forms of complex samples -- Sampling distributions for complex samples -- Using Stata's svy commands -- 8.2.3.Standard errors with nonresponse -- Unit; nonresponse and poststratification weights -- Item nonresponse and multiple imputation -- 8.2.4.Uses of standard errors -- Confidence intervals -- Significance tests -- Two-group mean comparison test -- 8.3.Causal inference -- 8.3.1.Basic concepts -- Data-generating processes -- Counterfactual concept of causality -- 8.3.2.The effect of third-class tickets -- 8.3.3.Some problems of causal inference -- 8.4.Exercises -- 9.Introduction to linear regression -- 9.1.Simple linear regression --
 
Contents note continued: 9.1.1.The basic principle -- 9.1.2.Linear regression using Stata -- The table of coefficients -- The table of ANOVA results -- The model fit table -- 9.2.Multiple regression -- 9.2.1.Multiple regression using Stata -- 9.2.2.More computations -- Adjusted R2 -- Standardized regression coefficients -- 9.2.3.What does "under control" mean? -- 9.3.Regression diagnostics -- 9.3.1.Violation of E(εi) = 0 -- Linearity -- Influential cases -- Omitted variables -- Multicollinearity -- 9.3.2.Violation of Var(εi) = α2 -- 9.3.3.Violation of Cov(εi, εj) = 0, i [≠] j -- 9.4.Model extensions -- 9.4.1.Categorical independent variables -- 9.4.2.Interaction terms -- 9.4.3.Regression models using transformed variables -- Nonlinear relationships -- Eliminating heteroskedasticity -- 9.5.Reporting regression results -- 9.5.1.Tables of similar regression models -- 9.5.2.Plots of coefficients -- 9.5.3.Conditional-effects plots --
 
Contents note continued: 9.6.Advanced techniques -- 9.6.1.Median regression -- 9.6.2.Regression models for panel data -- From wide to long format -- Fixed-effects models -- 9.6.3.Error-components models -- 9.7.Exercises -- 10.Regression models for categorical dependent variables -- 10.1.The linear probability model -- 10.2.Basic concepts -- 10.2.1.Odds, log odds, and odds ratios -- 10.2.2.Excursion: The maximum likelihood principle -- 10.3.Logistic regression with Stata -- 10.3.1.The coefficient table -- Sign interpretation -- Interpretation with odds ratios -- Probability interpretation -- Average marginal effects -- 10.3.2.The iteration block -- 10.3.3.The model fit block -- Classification tables -- Pearson chi-squared -- 10.4.Logistic regression diagnostics -- 10.4.1.Linearity -- 10.4.2.Influential cases -- 10.5.Likelihood-ratio test -- 10.6.Refined models -- 10.6.1.Nonlinear relationships -- 10.6.2.Interaction effects -- 10.7.Advanced techniques -- 10.7.1.Probit models --
 
Contents note continued: 10.7.2.Multinomial logistic regression -- 10.7.3.Models for ordinal data -- 10.8.Exercises -- 11.Reading and writing data -- 11.1.The goal: The data matrix -- 11.2.Importing machine-readable data -- 11.2.1.Reading system files from other packages -- Reading Excel files -- Reading SAS transport files -- Reading other system files -- 11.2.2.Reading ASCII text files -- Reading data in spreadsheet format -- Reading data in free format -- Reading data in fixed format -- 11.3.Inputting data -- 11.3.1.Input data using the Data Editor -- 11.3.2.The input command -- 11.4.Combining data -- 11.4.1.The GSOEP database -- 11.4.2.The merge command -- Merge 1:1 matches with rectangular data -- Merge 1:1 matches with nonrectangular data -- Merging more than two files -- Merging m:1 and 1:m matches -- 11.4.3.The append command -- 11.5.Saving and exporting data -- 11.6.Handling large datasets -- 11.6.1.Rules for handling the working memory --
 
Contents note continued: 11.6.2.Using oversized datasets -- 11.7.Exercises -- 12.Do-files for advanced users and user-written programs -- 12.1.Two examples of usage -- 12.2.Four programming tools -- 12.2.1.Local macros -- Calculating with local macros -- Combining local macros -- Changing local macros -- 12.2.2.Do-files -- 12.2.3.Programs -- The problem of redefinition -- The problem of naming -- The problem of error checking -- 12.2.4.Programs in do-files and ado-files -- 12.3.User-written Stata commands -- 12.3.1.Sketch of the syntax -- 12.3.2.Create a first ado-file -- 12.3.3.Parsing variable lists -- 12.3.4.Parsing options -- 12.3.5.Parsing if and in qualifiers -- 12.3.6.Generating an unknown number of variables -- 12.3.7.Default values -- 12.3.8.Extended macro functions -- 12.3.9.Avoiding changes in the dataset -- 12.3.10.Help files -- 12.4.Exercises -- 13.Around Stata -- 13.1.Resources and information -- 13.2.Taking care of Stata -- 13.3.Additional procedures --
 
Contents note continued: 13.3.1.Stata Journal ado-files -- 13.3.2.SSC ado-files -- 13.3.3.Other ado-files -- 13.4.Exercises.

Title Subject
Stata

Subject Term
Statistics -- Data processing.
 
Mathematical statistics -- Data processing.

Added Author
Kreuter, Frauke.

Electronic Access
Contributor biographical information http://catdir.loc.gov/catdir/enhancements/fy1302/2012934051-b.html


LibraryMaterial TypeItem BarcodeShelf NumberCopy
IIEMSAGeneral Books33168025594199519.20285 K79D 20121