年0606月月0101日，日，日，200820082008年第年第年第55期，总第期，总第7
7期编者按：很多人曾问及SAS ，Stata 和SPSS 之间的不同，它们之中哪个是最好的。可以想到，每个软件都有自己独特的风格，有自己的优缺点。本文对此做了概述，但并不是一个综合的比较。人们时常会对自己所使用的统计软件有特别的偏好，希望大多数人都能认同这是对这些软件真实而公允的一个对比分析。
SAS、SPSS 和Stata的比较
Special Issue
Comparison
Between SAS,SPSS and Stata
EpiMan Cluster 特刊：SAS、SPSS 和Stata 的比较
Special Issue
SAS、SPSS 和Stata 的比较
本期主编:epiman
本期审校:epiman
本期排版:epiman
2008年06月01日
2008年第5期
总第7期邮箱： 网址： 目录 第一部分：英文版 第一讲，英文版SA
S 第二讲，英文版Stata 第三讲，英文版SPSS 第四讲，英文版总结第二部分：中文版 第五讲，中文版SAS 第六讲，中文版Stata 第七讲，中文版SPSS 第八讲，中文版总结第三部分：网友评论
SAS、SPSS和STATA的比较
SAS
General u.SAS is a package that many"power urs"like becau of its power and programmability.Becau SAS is such a powerful package,it is also one of the most difficult to learn.To u SAS,you write SAS programs that manipulate your data and perform your data analys.If you make a mistake in a SAS program,it can be hard to e where the error occurred or how to correct it.
Data Management.SAS is very powerful in the area of data management, allowing you to manipulate your data in just about any way possible.SAS includes proc sql that allows you to perform sql queries on your SAS data files. However,it can take a long time to learn and understand data management in SAS and many complex data management tasks can be done using simpler commands in Stata or SPSS.However,SAS can work with many data files at once easing tasks that involve working with multiple files at once.SAS can handle enormous data files up to32,768variables
and the number of records is generally limited to the size of your hard disk.
Statistical Analysis.SAS performs most general statistical analys (regression,logistic regression,survival analysis,analysis of variance,factor analysis,multivariate analysis).The greatest strengths of SAS are probably in its ANOVA,mixed model analysis and multivariate analysis,while it is probably weakest in ordinal and multinomial logistic regression(becau the commands are especially difficult),robust methods(it is difficult to perform robust regression,or other kinds of robust methods).While there is some support for the analysis of survey data,it is quite limited as compared to Stata.
Graphics.SAS may have the most powerful graphic tools among all of the packages via SAS/Graph.However,SAS/Graph is also very technical and tricky to learn.The graphs are created largely using syntax language; however,SAS8does have a point and click interface for creating graphs but it is not as easy to u as SPSS.
Summary.SAS is a package geared towards power urs.It has a steep learning curve and can be frustrating at first.However,power urs enjoy the its powerful data management and ability to work with numerous data files at once.
Stata
General U.Stata is a package that many beginners and power urs like becau it is both easy to learn and yet very powerful.Stata us one line commands which can be entered one command at a time(a mode favored by beginners)or can be entered many at a time in a Stata program(a mode favored by power urs).Even if you make a mistake in a Stata command,it is often easy to diagno and correct the error.
Data Management.While the data management capabilities of Stata may not be quite as extensive as tho of SAS,Stata has numerous powerful yet very simple data management commands that allows you to perform complex manipulations of your data with ea.However,Stata primarily works with one data file at a time so tasks that involve working with multiple files at once can be cumbersome.With the relea of Stata/SE,you can now have up to 32,768variables in a Stata data file but probably would not want to analyze a data file that exceeds the size of your computers memory.
Statistical Analysis.Stata performs most general statistical analys (regression,logistic regression,survival analysis,analysis of variance,factor analysis,and some multivariate analysis).The
greatest strengths of Stata are probably in regression(it has very easy to u regression diagnostic tools), logistic regression,(add on programs are available that greatly simplify the interpretation of logistic regression results,and ordinal logistic and multinomial logistic regressions are very easy to perform).Stata also has a very nice array of robust methods that are very easy to u,including robust regression,regression with robust standard errors,and many other estimation commands include robust standard errors as well.Stata also excels in the area of survey data analysis offering the ability to analyze survey data for regression,logistic regression,poisson regression,probit ).The greatest weakness in this area would probably be in the area of analysis of variance and traditional mutivariate manova,discriminant analysis,etc.).
Graphics.Like SPSS,Stata graphics can be created using Stata commands or using a point and click interface.Unlike SPSS,the graphs cannot be edited using a graph editor.The syntax of the graph commands is the easiest of the three packages and is also the most powerful.Stata graphs are high quality, publication quality graphs.In addition,Stata graphics are very functional for supplementing statistical analysis,for example there are numerous commands that simplify the creation of plots for regression diagnostics.
Summary.Stata offers a good combination of ea of u and power.While Stata is easy to learn,it al
so has very powerful tools for data management,
many cutting edge statistical procedures,the ability to easily download programs developed by other urs and the ability to create your own Stata programs that amlessly become part of Stata.
SPSS
General u.SPSS is a package that many beginners enjoy becau it is very easy to u.SPSS has a"point and click"interface that allows you to u pulldown menus to lect commands that you wish to perform.SPSS does have a"syntax"language which you can learn by"pasting"the syntax from the point and click menus,but the syntax that is pasted is generally overly complicated and often unintuitive.
Data Management.SPSS has a friendly data editor that rembles Excel that allows you to enter your data and attributes of your data(missing values, value labels,etc.)However,SPSS does not have very strong data management tools(although SPSS version11added commands for reshaping data files from"wide"format to"long"format,and vice versa).SPSS primarily edits one data file at a time and is not very strong for tasks that involve working with multiple data files at once.SPSS data files can have 4096variables and the number of records is limited only by your disk space. Statistical Analysis.
SPSS performs most general statistical analys (regression,logistic regression,survival analysis,analysis of variance,factor analysis,and multivariate analysis).The greatest strengths of SPSS are in the area of analysis of variance(SPSS allows you to perform many kinds of tests of specific effects)and multivariate anova,factor analysis, discriminant analysis)and SPSS11has added some capabilities for analyzing mixed models.The greatest weakness of SPSS are probably in the abnce of robust methods(we know of no abilities to perform robust regression or to obtain robust standard errors),the abnce of survey data analysis(we know of no tools in this area).
Graphics.SPSS has a very simple point and click interface for creating graphs and once you create graphs they can be extensively customized via its point and click interface.The graphs are very high quality and can be pasted into other word documents or powerpoint).SPSS does have a syntax language for creating graphs but many of the features in the point and click interface are not available via the syntax language.The syntax language is more complicated than the language provided by Stata,but probably simpler(but less powerful)than the SAS language.
Summary.SPSS focus on ea of u(their motto is"real stats,real easy", and it succeeds in this area.But if you intend to u SPSS as a power ur, you may outgrow it over time.SPSS is strong in
the area of graphics,but
