ANALYZING QUANTITATIVE DATA WITH SPSS © Susan Mowers Spring 2016

Overview Working with quantitative data Introducing SPSS Elements of your descriptive analysis Before SPSS, check your data literacy: Who do the data cover? When/where was it gathered? Was it a sample, of whom? What do the data mean? Or in other words, the background story to your analysis, and the write-up of your methodology Descriptive statistics 101 Archive your work Weights Selected options for presenting data ICPSR data research materials for students… Quantitative analysis has two aspects: Descriptive statistics (Description or summarization of or showing the data at hand), According to the data from the 2006 Census, women are twice as likely to be single parents if they live in Ontario, and three times as likely in ??) , and inferential statistics (prediction), single parent mothers … On the other hand,

Learning outcomes Find out what files you need to do basic SPSS quantitative analysis Learn how to capture your files and your work Learn what elements you can use for a descriptive analysis of your quantitative data. Learn what learning tools ICPSR has to offer for quantitative research Capture your files and work –for working effectively and being able to back up your research results

Working with quantitative data You need to know the source and methods for your data What is the basic information, Statistics Canada web site: [StatsCan Page for the CCHS] What about the rest of the detail? See <odesi> for your data and documentation Why do you need to gather various files before you get started in SPSS? Understand what the data represent – Are they meaningful to your research question? Be prepared to answer how you arrived at your results – Are your results replicable / valid? Keep your work every day in one place! Double-check regularly: are your files backed up? Make sure the data license allows you to share your data with the rest of your research team and supervisor Describe your methodology: Cite your data!! Name your key variables / measurements. Are they different from the original data? Can you provide your SPSS code of your work to your professor or team-mates?

Introducing Spss Benefits of SPSS? Easy to learn All the benefits of the computing syntax code behind your GUI-driven statistics Designed for social science data SPSS supports labels, declared missing values and so on,(good data markup) e.g.,: Label: Legal Marital Status for the variable DHHGMS, Label: Married for the value 1, Common-law for the value 2, …. The labels will show up on your tables and graphs! Missing value: 9 = Not stated, required so that SPSS will treat 9 as a « missing value, and not as a valid value SPSS also supports weighting Caution: labels and missing values should be declared by the data producer/provider, but they still need to be checked. Non-SPSS file formats? Conversion! Make sure you retain SPSS installed in: Vanier labs, 3rd floor Morisset lab, and FSS Library (FSS 2010). SPSS = graphical – pull-down menus + syntax code to re-run … you and your supervisor or instructor or readers of your research articles can re-run your statistics Research replication Non-SPSS file formats ? Conversion options Can you import or transfer to SPSS .sav ? SPSS supports some « codebook information » Non-SPSS file formats? Conversion! Check to see if the original file has data labels? Note that .sav is a standard SPSS data file. .por is a portable SPSS file Labels are essential for your descriptive statistics which is partly about showing your statistics, either through statistical tables or in graphs!

DATA documentation QUESTIONNAIRE CODEBOOK

Must-have files for descriptive analysis using spss User guide is prefered over Statistics Canada survey page. It answers: SURVEY METHODOLOGY QUESTIONS: Does the survey cover the right population and time period? Who (target population, response rate) When data gathered/covered, Why, (e.g, health planning, policy and services) How (survey design/method) This is the background to your research story! Codebook, Questionnaire… They answer: What is the size of the sample? Does the survey cover the right concepts and measurements? Will you need to do more work (and how) on the data before it is ready to analyse? What is the weight variable? SPSS data file (either the full dataset or a subset) Note: http://uottawa.libguides.com/c.php?g=265010&p=3104224 Main products for descriptive statistics (SPSS, Stata, SAS, even Excel – note collectica version) Descriptive statistics describe, summarize and show the data – they don’t allow for predictions beyond the data

Analyzing quaNTITative data through descriptive statistics Descriptive statistics describe, summarize and show the data Do you know your types of data? Why does it matter? Averages won’t work with data that reflect qualitative / categorical values, e.g., « Gender » or « Highest education level », but they will work with quantitative values, e.g., « Positive mental health continuous scale », « Years of education » or « Earnings income (in dollars) ». Types of data? Nominal Married, Common-Law, Divorced-separated, Single/Never married Ordinal Less than high school, High school, Some post-secondary, Post-secondary grad. Interval-ratio $15,000 - $29,000 (as one of 10 levels of income, in equal income ranges of $14.999) Continuous 0-70 : Positive mental health continuous scale, Main products (SPSS, Stata, SAS, even Excel – note colectica version of Excel) Descriptive statistics don’t allow for predictions beyond the data itself Qualitiative variables: Numbers have no meaning, nominal groups are unordered, ordinal groups are ordered Quantative variables: numbers have meaning, spaces between numbers are equal

Importing data sources Documents (.pdf) SPSS file (.sav) Note, our SPSS file is a subset of the variables we are analysing Syntax file (.sps) Log/output file (.spv) The full file has 1381 variables, ours has xx including two new variables I created to prepare the data for this workshop.

Hands-on Import files to your work area Create a folder called spss on your computer desktop Go to http://bit.ly/spssgrad Right click on files.zip. Save the file to the desktop: Save target as and select Desktop Right click on files.zip and follow the instructions to Select a Destination and Extract the files.

Hands-on Open the data Under folder data Double-click on the file cchs2012_spssgrad.sav

Descriptive statistics 101 What do the data have to say about our categorical values? Use Frequencies for categorical values (e.g., maritial status, body mass index groups, education levels, …) For nominal values and ordinal values Distribution in raw numbers and percents (ratios), Select statistics: mode for nominal values Select statistics: median and mode for ordinal values Frequencies for age groups and education level The mode (most typical) Descriptives for Positive mental health continuous scale Cross-tabulation (percentages) two categorical variables BMI nominal overweight, underweight, just about right (do you considder yourself) Means Compares the average (mean) between groups Use when one variable is interval and the other is ordinal or nominal E.g. Who is higher educated, married men or married women? (married men/women is a recoded/derived value that I created)

Hands-on Let’s do a frequency table for a categorical value … chose from: Marital status – (G) DHHGMS (nominal) Body mass index BMI class (18 +) HWTGISW (ordinal) Highest education lev/ HH 4 levels EDUDH04 Note, I have filtered out respondents aged 12-17 years Data file: ages 18 and over

Menu method for frequency + USING paste to syntax (best practise) Click on Analyse Click on Descriptive statistics Click on Frequencies Select your variable, using the right arrow Click on Statistics Select Mode, and if relevant, Median Click Continue Click Paste Run your command in your Syntax editor (highlight and click on right arrow at top) FREQUENCIES VARIABLES=HWTGISW /STATISTICS=STDDEV MEDIAN MODE /ORDER=ANALYSIS.

WHAT ARE Sample weights? Unweighted Frequencies Describe the distribution of your survey respondents’ legal marital status Weighted Frequencies Describe the distribution of your target population’s (Canadians) legal marital status

Hands-on Turn on the weight Pull down menu: Data then Scroll down and select Weight cases Paste to your syntax editor Re-run your frequencies, pasting again into your syntax editor You now have population estimates for your data! Weighted frequencies can be used as research results We will keep the weight turned on for the rest of our descriptive statistics workshop. Best practise: by pasting your code into your syntax editor, you can clearly see if your data is weighted or not

Descriptive statistics 101 What do the data have to say about our continuous variables? Use a histogram for a continuous variable to show the distribution … Continuous variables: Positive Mental Health Continuous Score and Body mass index scale Note: Higher scores in the two categorical values above indicate higher levels of positive mental health and higher ratios of weight to height, so higher on the scale for overweight compared to underweight. Frequencies for age groups and education level The mode (most typical) Descriptives for Positive mental health continuous scale Cross-tabulation (percentages) two categorical variables Means Compares the average (mean) between groups Use when one variable is interval and the other is ordinal or nominal eg. Who has a more positive mental health score, men or women? Underweight = <18.5 Normal weight = 18.5–24.9 Overweight = 25–29.9 Obesity = BMI of 30 or greater

Hands-on Let’s do a histogram to show the distribution of positive mental health Positive Mental Health Continuous Score PMHDSCR (continuous) OR Body mass index scale BMI / self-report - (D,G) HWTGBMI Note, Respondents aged 12-17 years have been removed from the data

Menu method for frequency + USING paste to syntax (best practise) Click on Graphs Click on Legacy dialogs Chose Histogram Click on your variable of interest and use the right arrow Optional: If you want separate histograms for different groups, e.g., married and single, you can put an additional variable (e.g, Sex or Married respondents (not single)) in the Panel by: are. Chose rows if you would like the two graphs on top of each other, or Column if you want them side by side. Click on Statistics Click Paste Run your commands in your Syntax editor (highlight the commands and click on right arrow at top) GRAPH /HISTOGRAM=PMHDSCR /PANEL ROWVAR=MARRIED ROWOP=CROSS.

Show your data (descriptive statistics), e.g., histogram

Descriptive statistics 101 ACCORDING TO OUR DATA … Continuous variables, part 2 Run basic Descriptive statistics for continous variables, e.g. Click on Pull-down menu Analyse Click on Descriptive statistics Click on Descriptives Click on the continuous variable(s) you want, like Postitive Mental Health Continuous Score and click on right arrow Click on Options to the right. Select Minimum, Maximum, Mean (=average), and for more advanced users, Standard deviation Note: your weight should still be turned on. If not, turn it back on. Click on Paste, and then in Syntax editor, Run your syntax Frequencies for age groups and education level The mode (most typical) Descriptives for Positive mental health continuous scale Cross-tabulation (percentages) two categorical variables Means Compares the average (mean) between groups Use when one variable is interval and the other is ordinal or nominal eg. Who has worked longer at their job, men or women?

Descriptives Weighted:

Quick note: Standard deviation From Math is Fun: http://www.mathsisfun.com/data/standard-deviation.html “The Standard Deviation is a measure of how spread out numbers are” and “what is normal and more extreme”. From data on the height of group of dogs … Calculate the mean and variance Calculate the variance (square of differences), then average of the sum of differences)

Descriptive statistics 101 ACCORDING TO OUR DATA … Does marital status reflect gender differences in attractiveness (age, body mass index) and education level? Bar graph - Show Cross-tabulation - Summarize Frequencies for age groups and education level The mode (most typical) Descriptives for Positive mental health continuous scale Cross-tabulation (percentages) two categorical variables Means Compares the average (mean) between groups Use when one variable is interval and the other is ordinal or nominal eg. Who has worked longer at their job, men or women?

Hands-on Let’s use a bar graph for categorical variables

Descriptive statistics 101: Categorical variables, continued Create Bar graphs to show the relationship between two categorical variables one is a re-code: married men and married women Let’s compare age pyramids for married men versus married women Click on Graphs Select Legacy Dialogs. Chose Bar Click on Clustered Click on Define Click on % of cases Select Married by gender > Category axis Select Age – (G) > Define Clusters by Click Paste and Run in your Syntax editor as usual

CLUSTERED AGE GRAPH for Married men vs. Married women (AGE PYRAMIDs)

Hands-on Let’s use Summary statistics to compare distribution of age groups of married men versus married women Cross tabulation

Descriptive statistics 101: Categorical variables, continued Create a cross tabulation to show correlation between two categorical values Let’s compare summary statistics of age groups for married men versus married women Click on Analyse Select Descriptive statistics Choose Crosstabs Select Age – (G) > Rows Select Married by gender > Columns Click on Cells Unselect Observed for Counts Click on Column for Percentages Click on Continue Click Paste and Run in your Syntax editor as usual

Descriptive statistics 101: Categorical variables, last slide Note: you could group age groups into 15 year intervals for example, for a simpler crosstab

reSources for your research projects Where to find data and its must-have documentation? Odesi – Canadian ICSPR – International Ask me: Susan Mowers, Your Data Librarian smowers@uottawa.ca or gsg@uottawa.ca © Susan Mowers 2016