stata 介绍与命令

Introduction to StataGetting Data Into StataThere are three ways of getting data into Stata1.direct keyboard entry using the Stata EDITOR2.read raw data (ASCII files) directly into a Stata dataset (Stata can import tab or commadelimited data or data in fixed column format)e a data transfer program such as DBMScopy or Stat/Transfer (we use Stat/Transfer) whichcan convert data from almost any common program (database, spreadsheet or statisticalpackage) into Stata and vice versaTyping Commands vs Using Menus vs Batch FilesThere are three ways that you can run Stata.1.choose commands from the drop-down menus2.type commands in to the “Command” box3.type a set of commands into a small file (called a -do- file) and then run the whole set ofcommands at once.Ultimately, you want to use -do- files for all of your research work because it is the only way that you can exactly reproduce any analyses that you have done. To move you in this direction, we will primarily use the “Command” box (ie type in commands), but if you are stuck, you can use the menus.21 Small Steps to Get You StartedThe following table outlines 21 simple steps that will get you started using Stata. These exercises use a dataset (nocardia.dta) that has already been saved in Stata format. These data are a subset of the data from a case-control study of Nocardia mastitis carried out in Nova Scotia. A description of the dataset is attached below.10 More Steps .... To Make You an Expert5 Challenge Steps1.What is the average herd size of herds that use, and don't use, cloxacillin based dry cowproducts?2.Does there seem to be any association between using neomycin products and cloxacillinproducts?3.Is the distribution of milk production levels approximately “normal”?4.What is the average herd size of herds that had a bulk tank SCC over 200,000 cells/ml?5.What is the variance of log-transformed bulk tank cell counts in herds that had more than 40cows?If you can complete these challenges ..... you truly are an expert!Stata Command SyntaxExamplessummarize age weightthis will compute summary statistics for the variables “age and “weight”summarize age weight if farm == 17summary statistics, but only for pigs from farm # 17by sex : summarize age weight if farm == 17separate summary statistics for each sex of pigs on farm # 17by sex : summarize age weight if farm == 17 , detailsame as above, but provide more detailed summary statisticsNotes:specifying a range of numbers1/5 is the same as 1 2 3 4 5specifying a list of variables farm1 - farm3 is the same as farm1 farm2 farm3 single =for assigning a value (eg. generate var5=12.5)double ==for checking if two things are equal (eg. sum xxx if var5 ==12.5)missing value is “ .”Data Manipulations in StataCreating New Variables in Statagen (generate)This command creates a new variable according to an “expression” that you type in.gen newvar = oldvar- this just copies oldvar intonewvargen age2 = age^2- new variable “age2" equals“age” squaredegen (extension to generate)This command also creates new variables but has a whole lot of ‘pre-programmed’ features to carry out special tasks.egen rankx = rank(x)- creates a new variable “rankx”that contains the rank ordering of the original variable “x”Creating “Dummy” (or indicator) Variables in StataWe often want to change a categorical variable into a series of “dummy” variables. We do this by putting the “xi:’ prefix before a Stata command and then putting “i.” before each categorical variable that needs to be converted to “dummy” variablesxi:‘expanded interaction’- a command that creates dummy variables for use in any Stata command- put “xi:” before the command- put “i.” before the variable(s) to be “dummied”- e.g. xi: regress prod bscc i.dout- this regresses prod on:–bulk tank SCC (a continuous variable)– a series of 3 dummy variables describing the herds level of outdoorexposure for dry cowsChanging the Contents of a Variable in StataeditUse the on-screen editor (that looks sort of like a spreadsheet)replaceThis command replaces the contents of an existing variable according to some expressionthat you type in.replace xyz = . if pqr == 23- this replaces all values of “xyz” with a missing value IF the value of pqr = 23. (Note thedouble ‘=’).recodeThis command changes specified values a variable to a new value.recode scc 1/199=1 200/399=2 400/9999=3- this changes scc from a continuous variable into a categorical variable with 3 levelsegen cutThis command creates a categorical variable from a continuous variableegen scc_cat=cut(scc), at(0 200 400 9999)- this does the same as the previous example, except that it creates a new variable (scc_cat) instead of replacing the contents of the original variable. This is safer since it doesn’t destroy your original data. The “ at(# # #) “ tells Stata where the boundries for the categories are. (Note: these are just a few examples of how to manipulate variables in Stata. See the on-screen help or the manuals for a more complete description of these codes and for other variable manipulation codes).Linear Regression in StataThe following notes only describe a few of the features of Stata that relate to linear regression. They are not intended to replace either the on-screen help, or the manuals.regress depvarname indepvarlist- basic linear regressionpredict newvarname, options- this will calculate a wide range of diagnostic values for assessing regression models predict predval, xb- (computes a new variable “predval” containing the pred. values)- some of the more commonly used options are as follows:Stepwise Linear Regression in StataCommand Syntaxsw reg depvarname indepvarlist, optionssw- is the commandreg- tells it you want linear regression (later we will use it for logistic regression by replacing reg with logistic or logit)depvarname is the name of the dependent variableindepvarlist is the list of independent variablesx1 x2 x3 x4 x5 x6 x7- all are treated as separate variablesx1 x2 (x3-x6) x7- x1 x2 and x7 are treated as separate variables and variables x3 to x6 are moved in or out of the model as a single termx1 x2 i.x3- the dummy variables created in i.x3 will be moved in or out asa block (this assumes that you put xi: before the command)Optionspr(#)- specify the p-value for removal eg. pr(0.05)pe(#)- specify the p-value for entryforward- specify forward selection (rether than backward elimination)lr- use the likelihood ratio test rather than Wald’s test for testing terms in logistic regressionhier- carry out hierarchical regression (check for term to enter or remove based on the order they are listed in the command line)lockterm- always keep the first term { ie a variable or a group of variables enclosed in () } in the model)(other options that relate to the regress or logistic commands can also be used)pr(#)-backward eliminationpr(#) hier- backward elimination in hierarchical mannerpr(#) pe(#)- stepwise (starting with a full model)pe(#)- forward selectionpe(#) hier- forward selection in hierarchical mannerpe(#) pr(#) forward- stepwise (starting with a null model)The Essential Features of Stata。