Have you experienced any adverse health effects from the sun? Yes 1 No 2 Unsure 3

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1 This session takes you through some more of the statistical tests available in SPSS, as well as the use of syntax. It uses the Health 2011 data file. The questionnaire from which the data file was created was provided in the Intermediate Guide to SPSS handout. 1 Multiple Response Questions There are two multiple response questions in the data that will be used for this exercise. They are questions 14 and 15: Q14 Have you experienced any adverse health effects from the sun? Yes 1 No 2 Unsure 3 If you answered YES to question 14, please list the three main adverse effects Q15 Is it possible to get sun burnt: YES NO On a cloudy day? 1 2 Through clothing? 1 2 Through closed car windows? 1 2 In the shade? 1 2 While swimming? 1 2 The main items of interest will be the adverse effects listed as the second part of question 14. Twenty different things were listed overall by the respondents and were subsequently manually coded 1 to 20. This will be important to know when setting up the multiple response data because a distinction is made between categorical data and dichotomous data. Question 15 is an example of dichotomous data because each of the subparts can only be answered yes or no that is, in one of two ways. When the data is entered into an SPSS data file, each item of data will be a variable. The second part of question 14, asks for three possible adverse effects, so three variables were necessary (q14.1, q14.2, q14.3). Question 15 has five subparts so five variables need to be created (q15.1 to q15.5). Page 1 of 21

2 1.1 Creating and using Multiple Response sets with Custom Tables In order to process each of these questions as blocks of information, rather than separate variables, multiple response sets need to be defined as the first part of the process. There are two ways of creating multiple response sets in SPSS. One of the ways (the Multiple Response option in the Analyze menu) does not retain the definitions between SPSS sessions. The other does as long as the data file is saved once they have been created; it is this latter way that is used in this exercise. There are two ways to access this method using the menu options in SPSS, the first of which is by selecting: Data Define Multiple Response Sets The second way is by selecting: Analyze Tables Multiple Response Sets Either way, you should then do the following in the Define Multiple Response Sets window: move the three variables containing the listed effects (q14.1, q14.2, q14.3) into the Variables in Set panel click on Categories (because the responses were coded into different categories) give the set a Name (e.g. q14adv) give a Label to this set (e.g. Adverse health effects from the sun) click on Add Page 2 of 21

3 The set for question 15 can be created at the same time but this time the variables are dichotomous and the answers of interest are the Yes ones coded 1. move the five variables relating to question 15 into the Variables in Set panel click on Dichotomies enter the counted value as 1 give the set a Name (q15) give a Label to this set (Ways of getting sunburnt) click on Add Both sets will now be listed in the Multiple Response Sets panel click on OK Note: to view the variable names rather than labels in the list of variables, as shown in the two diagrams above, from the main menu select: Edit Options Use the toggle to switch to the Display Names option in the Variable Lists section of the Options window that appears Page 3 of 21

4 Once you have created the multiple response sets some output will appear in the results window (not given here) detailing the variables used. The two sets will not be visible in the data file, except as the separate variables making up the sets, but they are set up for use in any of the Tables procedures. The sets will be retained for this use if the data file is saved before ending the SPSS session. To use these sets in Custom Tables, from the menus choose: Analyze Tables Custom Tables A warning box will appear reminding you that all your variables should be set appropriately in the Measure column under Variable View. click on OK The Custom Tables dialogue box is arranged differently to most other procedures in that it has a Canvas area where specifications are dragged and dropped to build the required table. The concept is similar to using Chart Builder for producing graphs. The multiple response sets that have been defined will be listed at the end of the other variables in the panel on the left hand side: The icon with four squares depicts a category set while the one with two squares is for a dichotomous set. To create a frequencies table for the q14adv set: click on q14adv drag and drop it into the Rows panel Page 4 of 21

5 A mock-up of the table appears in the canvas. Note there are no percentages or totals given automatically. To include percentages on the table: click on Summary Statistics... click on Column Percent select Column N % use the arrow head to move it into the Display box click on Apply to Selection click on Close To include a total on the table: click on Category and Totals... click on Total in the Show box on the right hand side Page 5 of 21

6 click on Apply The canvas will now show the table with percentages and a total included. click on OK The resultant table should look like: $q14adv Adverse health effects from the sun Count Column N % Burns % Chapped lips 2 4.7% Blisters % Heat stress 1 2.3% Freckle/mole discol 2 4.7% Mole removal 1 2.3% Melanoma 1 2.3% Lesion excision 2 4.7% Headaches 2 4.7% Sunstroke 4 9.3% Moles 2 4.7% Heat stroke 3 7.0% Dehydration 1 2.3% Heat exhaustion 1 2.3% Peeling % Growth removal 1 2.3% Tired 3 7.0% Sickness 1 2.3% SCC 2 4.7% Skin rash 4 9.3% Total % Page 6 of 21

7 Note that the percentages are automatically based on the number of valid cases i.e. those people who answered the question by giving at least one adverse health effect. The tables for dichotomous multiple response sets are created in exactly the same way. To create a two-dimensional table, similar to a Crosstabs table, the second variable would be dragged and dropped into the Columns panel. Row or column percentages can then be chosen as required. 1.2 Graphing Multiple Response Data Using Chart Builder is the only way to create graphs of multiple response data. Once the sets have been defined they can be used just like normal variables on the Chart Builder canvas. To create a Bar chart of the multiple response set q14adv, from the menus choose: Graphs Chart Builder click on OK to say the all variables have been defined appropriately drag the simple bar chart image onto the canvas drag the q14adv set and drop it on the X axis By default, counts will be represented by a bar for each category. To change this to percentages the Statistic in the Element Properties dialogue box has to be changed. If the graph was of a simple variable, the percentages would need to be based on the total number of cases represented. With a multiple response set, though, there is the possibility that every case could be included in every bar and this has to be allowed for when requesting the appropriate percentage base. To specify the correct percentage calculation, in the Element Properties dialogue box: choose Response Percentage from the drop down list in the Statistics area Page 7 of 21

8 click on Apply click on OK The resultant chart will look like: It can be edited in the normal way to create the desired image. 2 Data Manipulations 2.1 Converting a String Variable to Numeric Whilst SPSS will happily allow alphabetic / string information to be entered as part of the data file, the more in-depth statistical analysis procedures require numeric data only, even if those numbers are simply codes or values representing categories At the questionnaire design stage, though, it may be very difficult to anticipate the responses that will be given so creating a tick-box type question can be too complicated, hence the use Page 8 of 21

9 of a write the answer on the line instruction. The choice then is to either numerically code the data before keying it in, or to enter the response words as given. The Automatic Recode facility in the software is provided to assign a value or code to each unique response. This facility, however, is NOT suitable for responses of more than two or three words. Towards the end of the Health data file there is a variable called q13 where respondents were asked: Who is the main person in your family that you would turn to for help with a problem? (Write the answer on the line provided) The variable is defined as String under Variable View and contains the one word answers given by the respondents. By definition it is a nominal variable and a Frequency table of the responses would look like: q13 Who turn to for help Frequency Percent Valid Percent Cumulative Percent Valid brother Dad father Father mother Mother Mum sister Sister Uncel Uncle Total The output shows only five different people that a respondent would turn to but, because of different spelling and different use of upper and lower case characters, eleven different responses are listed. To reduce this eleven down to the real five, the different categories need to be combined, i.e. recoded. Recoding string data is not straight forward, but turning it into numeric data and then using the standard Recode to combine the numbers is easy. To convert from string to numeric data, from the menus choose: Transform Automatic Recode... In the dialogue box that opens move q13 into the Variables box Because SPSS will be creating a new numeric variable from the original string one, it needs to be given a name, so: enter support_person in the New Name box Page 9 of 21

10 click on Add New Name select Treat blank string values as user-missing click on OK The resultant output should look like this: q13 into support_person (Who turn to for help) Old Value New Value Value Label brother Dad father Father mother Mother Mum sister Sister Uncel Uncle 1 brother 2 Dad 3 father 4 Father 5 mother 6 Mother 7 Mum 8 sister 9 Sister 10 Uncel 11 Uncle The original responses have been sorted into alphabetical order and assigned a value from 1 to 11. The original data has been used to create the Value Labels for those values and all this has been put into a new variable on the end of the data file called support_person. The different values can then be reduced to the five required ones by using the standard Recode into Different Variables command. Page 10 of 21

11 2.2 Computing a New Piece of Information Part of the aim of the Health questionnaire is to examine people s life satisfaction. However it is not appropriate to just ask the question What is your life satisfaction score? because noone would know how to answer. Instead, questions 9 to 12 of the questionnaire are items identified as contributing to overall life satisfaction. The respondent is asked to rate each of those items on the same basis (i.e. low number code for bad end of the scale and high number code for the good end of the scale) and then the four variables are totaled to come up with an overall life satisfaction score. To ask SPSS to do the calculation, from the menus choose: Transform Compute variable The target variable will have the result of the computation in it and, since it is a life satisfaction score, give it the name of lifesat. The numeric expression which will perform the calculation is: q9 + q10 + q11 + q12 because we want to add those four variables together. Either by typing it directly into the Numeric Expression box or moving the variables and addition sign into the box, specify the equation. click on OK The new variable lifesat will have been added to the end of the data file. Running the Frequencies procedure on this new variable shows that there are only 78 life satisfaction scores, when there are 80 cases in the data file. Looking at the actual data reveals why; the data in row 30 is missing for all four of the original variables, and the data in row 31 is missing for q10 and q12. Using the form of the numeric expression shown above, it will only be executed for those cases that have complete data. Since rows 30 and 31 contain missing data, the new variable lifesat is not computed for them. To create a total variable such as lifesat whether there is missing data or not requires a different numeric expression within the Compute command. Page 11 of 21

12 Specifically, you need to use the sum function (i.e. sum (q9, q10, q11, q12)); this will add any numbers that are present in the variables specified rather than ignoring any case that has missing data. Even when using the sum function, row 30 in the data file would still not have a lifesat score because all variables were missing, but row 31 would have a total of 6 (4 + 2). We will compute another life satisfaction variable using the sum command as above in the syntax section of this document. If the requirement had been to find a mean score for lifesat rather than a total, the numeric expression could have been: (q9 + q10 + q11 + q12) / 4 but the same constraints would have occurred because of the missing data. To calculate a mean of the values that are present in the variables use: mean (q9, q10, q11, q12) This will result in the numbers that are there being added together and divided by the number of numbers ie. (2 + 4) / 2 for row 31. There would still not be a result for row 30 as all the data is missing. The new variables created as a result of a computation can be used in any appropriate way in any part of the software. For example, to find out if there is a significant difference between the mean of the lifesat variable for those with children and those without children conduct a two (independent) samples t test. The results of this test should be as follows: T-Test Group Statistics q4 have children N Mean Std. Deviation Std. Error Mean lifesat yes no Independent Samples Test lifesat Equal variances assumed Equal variances not assumed Levene's Test for Equality of Variances F Sig. t df Sig. (2- tailed) t-test for Equality of Means Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Page 12 of 21

13 3 Syntax Syntax is the means of giving instructions to the SPSS software separately from, or in conjunction with, the menu system. Syntax is composed of commands that instruct the software how to manipulate and analyse your data. There are data definition commands that are used to read data from an external source and describe it procedure commands that perform the statistical analysis of the data data transformation or data modification commands that modify existing variables or create new ones In pre-windows days, syntax was the only way to drive the software and, for the most part, commands that were in use then will still work today with only minor changes. The Windows environment is just the user-friendly interface that makes using the software easier for human beings. The computer / software needs a more rigid set of instructions to be able to complete its tasks. Those instructions can be created and / or stored in the syntax file. It can be created by pasting commands that you have built up using the dialogue boxes by editing the commands that you have already pasted to create new commands by copying and pasting from commands that are displayed in your log / output file from scratch by typing commands directly into it a combination of any or all of the above The advantages of using a syntax file include keeping a record of all the processes you have gone through with the data having a set of commands that can be repeated regularly e.g. monthly reports building a set of instructions that can be used to test different portions of data as it arrives having options available that are not there under the menus (not included in this seminar) automating your processes 3.1 Using the Dialogue boxes to create the Syntax The syntax, or command language, used by SPSS is as close to English as any computer language is likely to be. What you say you are going to do is almost the same as the syntax you would use to do it. For example, we are going to ask for a frequency table for the variable q1 and put the instruction into the syntax file. To do this, from the menus choose: Analyse Descriptive Statistics Frequencies move q1 across into the Variables box Page 13 of 21

14 click on Paste (rather than OK) The procedure will not be executed, because you didn t click on OK, so you won t get a results table. Instead a new window is opened automatically the syntax window and the command you created via the dialogue box is written to that file. It will look like: FREQUENCIES VARIABLES=q1 /ORDER=ANALYSIS. The first part is what we said we wanted frequencies for the variable q1. Experience and experimenting will show you that SPSS will insert (sub)commands into the syntax that you did not click on specifically. These are the default settings that happen when you use the dialogue box and typically relate to handling of missing data or the choices under the options button shown on the dialogue box. As a general rule of thumb, if you didn t have to click on something to get it, you don t need to specify it in the syntax file because it is the default anyway. We didn t specifically request anything to do with the order so it is a default setting, so we don t actually need it. The shortened form of the command: FREQUENCIES VARIABLES=q1. will work in exactly the same way. Once the command is in the syntax window it can be edited to add extra variables, copied and pasted to create new instructions and then edited, or used as the model for another command that you type in. 3.2 Rules for Syntax Once you get into the realms of changing or entering your own commands though, you need to be aware of the requirements of syntax. The basic rules are: Page 14 of 21

15 The first word of the command (Frequencies in the example above) should probably start on the extreme left hand side of the line as this will make reading the syntax file easier in the long run Every new command starts on a new line The end of the command is signaled by use of a full stop (.) The command may be short and fit all on one line or you may choose to type it over several lines (as per the pasted Frequencies above). The continuation lines need to be indented at least one space (use Tab instead of a space and it will make the commands stand out really clearly) You can include comments in the file by starting a line with at least one asterisk (*) and finishing with the full stop You can leave blank lines between commands to aid readability but must not embed a blank line within a command Just as you would leave spaces between words in a sentence, you need to leave spaces between the items in the command Upper or lower case can be used or a mixture of both Generally, the commands can be abbreviated to the first four letters as long as they are unique to that command Variable names cannot be abbreviated Commas or spaces can generally be used to separate names of variables in a list The following examples all do exactly the same thing: frequencies variables=q1. FREQUENCIES VARIABLES=Q1. frequencies variables = Q1. frequencies variables=q1. FREQUENCIES VARIABLES=q1 /ORDER= ANALYSIS. freq vars = q1. Freq q Running Commands from Syntax The syntax window has the one special menu that is pertinent to it only the RUN menu. It is by using this menu that you instruct SPSS to run the commands in the syntax file and to produce the results you have requested. There is also a Run icon ( ) that will achieve a similar effect. The options under the RUN menu are All run all the commands that are in the current open syntax window Selection run only the command(s) that have been highlighted in the syntax window, or the command where the cursor currently is Page 15 of 21

16 To End run the commands from where cursor currently is to the end of the syntax file Step Through run the commands one at a time starting from the first command in the syntax window (Step Through From Start) or from where the cursor currently is (Step Through From Current). After a given command has run the cursor advances to the next command and you continue the step through process by selecting Continue Using the Run icon ( ) is equivalent to running Selection. Since there is only one command in the syntax window, from the menus choose: Run All The requested frequency table for q1 will be created in the output window. 3.4 Editing Commands in the Syntax File To go back to the syntax file / window, locate the Syntax file / page along the bottom of the screen and click on it, or use the Window menu as preferred. Using the command that is already in the syntax as the model for new commands: ask for a frequencies for both q1 and q2 remove the unnecessary ORDER subcommand line type in a new command line asking for frequency tables for the four life satisfaction and health questions (q9, q10, q11, and q12) The syntax file should read something like: FREQUENCIES VARIABLES=q1 q2. frequencies variables=q9 q10 q11 q12. Because the four variables are consecutive in the data file and we want tables for each of them, the last command could have been: frequencies variables=q9 to q12. The word TO is a reserved word in SPSS (meaning you can t use it as a variable name) and specifies the range of variables to be processed including the ones that are specified as first and last i.e. from q9 to q12 inclusive. To run these commands individually, place the cursor somewhere in the first command and then choose from the menus: Run Selection Page 16 of 21

17 Frequencies tables will be produced for q1 and q2. Now position cursor somewhere in the second command and click on the Run icon ( ) Frequency tables will be produced for questions 9 to 12. Using the dialogue box and the Paste technique, create the command for a Crosstabs table of q1 by q2. Ask for the expected count, row and column percentages to be included in the cells and ask for the Chi-square statistic to be included also. The syntax file will now contain the following: CROSSTABS /TABLES=q1 BY q2 /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT EXPECTED ROW COLUMN /COUNT ROUND CELL. Run this command only (use the icon or Run Selection from the menu). Copy and paste the command and edit it so that you get a table of q6 by q1, with percentages and Chi-square. The lines which begins /FORMAT and /COUNT are defaults so can be deleted. NOTE: The /COUNT line is the last line in the syntax and so contains the required full stop which heralds the end of the overall command (Crosstabs in this example). When you remove that line you MUST put the full stop back in, perhaps on the end of the previous line or on a line of its own, otherwise you will get an error and the command won t run as expected. Run this new command only. The syntax file that you have built up can be saved in the normal way and re-opened and added to as necessary. The corresponding data file needs to be open before the syntax can be run. 3.5 Including Commands in the Log / Output File The syntax commands can also be included as a part of the output file. This may need to be requested (depending on which version of the software being used) by adjusting the system settings in the following way. From the menus choose Edit Options click on the Viewer tab click on Display commands in the log Page 17 of 21

18 click on OK Until you turn off that request by going back and un-clicking it, all the commands that you run, either from the syntax or through dialogue boxes, will be listed as part of your output file. This can be an easy way of learning what the syntax commands look like and it can be a great way of trying something, examining the output, and only creating the syntax when you have achieved exactly the desired result / output. As a basic example, run an independent samples T-Test to see if there is a significant difference between the pre-diet weight of those respondents with children and those without. To do this, from the menus choose: Analyse Compare means Independent Samples T-Test make the Test variable q7 the grouping variable is q4 click on Define groups Group1 should be a 1 representing the group that has children Group 2 should be 2 representing the group that do not have children click on Continue click on OK Page 18 of 21

19 The resultant output should look something like: T-TEST GROUPS=q4(1 2) /MISSING=ANALYSIS /VARIABLES=q7 /CRITERIA=CI(.95). T-Test The output, of course, is exactly what we wanted, so to transfer the T-test command from the output file to the syntax file: double click on the piece of syntax to select it select the syntax lines right mouse click and choose copy go to the syntax window and position cursor where you want the command to go right mouse click and choose paste The font and size may not be the same as the other commands in the syntax file but that is immaterial as far as SPSS is concerned. The new command can now be copied and edited in the same way as any other one. Following on from previous information, we didn t specify anything to do with missing values or criteria in the dialogue box, so these subcommands are displaying default settings and can be removed without consequence. The shortened form would be: T-TEST GROUPS=q4(1 2) /VARIABLES=q7. The important thing to remember always is IF YOU REMOVE THE LAST LINE FROM A COMMAND THAT HAS BEEN CREATED BY SPSS ITSELF, YOU WILL ALSO BE REMOVING THE VITAL FULL STOP AT THE END. YOU MUST TYPE IT IN AGAIN BEFORE RUNNING THE COMMAND. Page 19 of 21

20 3.6 Typing Commands in the Syntax File from Scratch To open a new syntax file, from the menus choose: File New Syntax The task is to: compute a new variable by using the sum function on the four variables q9 to q12 (call it lifesat if you don t mind writing over the lifesat variable created previously; otherwise call it something similar) find the minimum, maximum, mean and standard deviation (the descriptive statistics) for the new variable lifesat form two groups by recoding lifesat into another new variable called lifesatgr; one group up to and including the mean, and one above the mean label the new variable names appropriately label the new group values appropriately crosstab the new grouped variable (lifesatgr) by q1 (gender), ask for the row and column percentages to be put in the cells, and get the Chi-square statistic insert a comment line with today s date before all of this syntax When you know what command to use but you are not sure of the exact format required you could ask SPSS for assistance by using the syntax help icon at the top of the syntax window. Just type in the first word of the command you want to use then click on the icon: The general form of that command will then be displayed for you to, hopefully, give a clue as to how to proceed: Page 20 of 21

21 Closing the help window will take you back to your syntax. The syntax to complete the tasks should read something like: ************* today s date *************. compute lifesat = sum(q9 to q12). descriptives variables=lifesat. (the output will display a mean of which you need for the next part) recode lifesat (lo thru = 1)(15.04 thru hi=2) into lifesatgr. variable labels lifesat Life satisfaction and health score lifesatgr Life satisfaction and health score (grouped). value labels lifesatgr 1 Below the mean 2 Above the mean. crosstabs tables= lifesatgr by q1 /cells = count row col /statistics=chisq. The line spaces between each command are optional but make the file much easier to read. By using the tab key to indent the second and subsequent lines within each command, the command line itself stands out again for ease of reading. The syntax would be run just like any other command by command, any part of the file, or all the file. Note that the software is generally rather lazy and won t actually do such things as computing the new variable, or recoding it, until you actually use it in a statistical procedure. You will know that there are tasks waiting to be completed because the message Transformations pending will appear along the bottom of the various SPSS windows. To make the transformation actually happen, either go to the Transform menu and click on Run pending transformation or run a procedure that uses the new variable, such as the descriptives in the example above, or use the command Execute after the transformation commands, for example compute lifesat = sum(q9 to q12). execute. The Execute command causes the data to be read and processed immediately so should be used sparingly if the data file is very large as it can be time consuming. Page 21 of 21