(Opens in a new tab) PDF on the Comprehensive R Archive Network website. The value labels are retained but original numerical values are replaced by index numbers 1, 2. However, when this is done, the variables of the item type are transformed into the type factor. The data can also be transformed into a more commonly used type data frame with the command df <- as.ame(ds). Numerical values can be saved as a separate variable by using the command q1 <- as.numeric(ds$$q1). Similarly, the command codebook(ds) displays the frequency tables of all variables. Numerical values corresponding to value labels can be checked with the command codebook(ds$$q1), which displays the frequencies of variable q1. The type of individual variables in the data is item, which contains both the values and value labels of a variable. This command creates an object ds, whose type is data set. Codebook of the WVS surveys or browse the codebook variables online. Īfter loading memisc, SPSS Portable file can be opened by entering the command ds <- as.t(('D:/data.por')). In order to merge with EVS you may wish to convert their SPSS file to the same. If desired, the installation directory can also be manually chosen by invoking the command install.packages('memisc', lib='D:/R_lib') ,Īnd loaded for use with the command library('memisc', lib.loc='D:/R_lib'). In order to open portable files (*.por), you need an R package memisc, which can be installed, for instance, from the RGui menu Packages → Install Package(s) or by entering the following command on the command line of R:Īfter installation, the package is loaded into the R session by using the command library('memisc'). 'D:/R_lib') may need to be changed to match the setup on your computer. This guide describes how a quantitative data file downloaded from FSD’s Aila Data Service is opened in R. Use the codebook provided in the appendix at the back of the Manual to guide you.(Opens in a new tab) is a free software environment designed for statistical computing and graphics. You will need to open the survey.sav data file. Use the codebook provided in the appendix at the back of the Manual to guide you.Ģ.4 Using the instructions provided in Chapter 5 of the SPSS Survival Manual, check the following continuous variables for out-of-range cases. These exercises give you practice with the process of screening your data and correcting errors.Ģ.3 Using the instructions provided in Chapter 5 of the SPSS Survival Manual, check the following categorical variables for out-of-range cases. It is very important that you check your data file for errors before beginning statistical analyses. When you have finished, enter some pretend data-you can generate this data yourself by completing the survey presented in the appendix at the back of the Manual. Follow the procedures described in Chapter 4 to define each of the variables listed in the codebook. Use this codebook to set up a data file from scratch. At the back of the SPSS Survival Manual you will find a codebook for survey.sav (the file that was used to generate some of the output throughout the book) and the questionnaire that this came from. (c) If you wished to change the format used to display the output tables, where in the Options would you do this?Ģ.2 The best way to learn how to set up an SPSS data file is to actually work through each of the steps yourself. (b) How do you change the number of decimal places that are used as the default for new variables? alphabetical order instead of file order)? (a) How do you change the order in which your variables are displayed (e.g. Use the following questions to review this material. This is covered at the start of Chapter 4 of the SPSS Survival Manual. Creating a data file and entering dataĢ.1 Before you start using SPSS to prepare a data file and run analyses, it is important to check the SPSS Options. Practice exercises Part Two: Preparing the data fileīefore attempting these questions read through Chapters 4 and 5 of the SPSS Survival Manual.
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