SPSS Propensity Score Matching: An overview AnnMaria De Mars The Julia Group Hi. Ph.d. Taught stats 27 years. Stat consultant 27 years . President. Pepperdine Prof. Blah blah blah

Let me tell you what we’re going to do … Overview of PSM Review logistic regression PSM with quintiles PSM with nearest neighbor FUZZY match I will probably go over everything twice, and yes, I know I am doing that. It’s like when you take statistics and read the textbook. It all seems to make sense until you try to do the problems. Or, you can do it in class when the professor is there and you go home and can’t because you forgot a step.

Why ? Non-equivalent groups are being compared, e.g, hospitals with & without specialized trauma centers Are differences due to patient characteristics or to hospital characteristics Propensity score matching is used when non-equivalent groups are being compared. For example, hospitals with specialized trauma centers have higher mortality than other hospitals, however, they also see patients with more severe conditions.

What ? Propensity score is the conditional probability of receiving a treatment given pre-treatment characteristics The propensity score match can simultaneously control for several different variables on which treatment groups differ. So, given the condition that you are, say, a burn victim, under age 10 and female what is your probability of being seen in a trauma unit? What’s the probability of being seen in the trauma unit given the conditions that the patient is 16-25, male and has a gun shot wound

When? Propensity scores are ideally used when there is substantial overlap in the groups. If those matched are the most extreme high scorers from one group and the most extreme low scorers from the second group then neither is representative and the results are suspect. In this it is similar to Analysis of Covariance. You can’t take a class of gifted children, another class of children with mental retardation, covary for IQ and compare them. The differences are just too great.

How? Step one: A logistic regression is performed with group as the dependent variable. A propensity score is created for each subject giving their likelihood of being in group one or group two.

Step Two There are two options for step two. Either subjects can be grouped by scores, usually into quintiles, or matched by propensity scores.

Step Three: Quintiles Perform a regular regression analysis with group (quintiles) as a covariate? -No, not the best way. People do it when they have a small sample and are worried about losing data. But it’s not advisable.

Step Three, Option 2: Match Match subjects on propensity scores & perform a regular regression analysis on this subsample 1,000 subjects from rural hospitals matched with 1,000 subjects from urban hospitals who have the same propensity score

So simple, a child can do it? Two out of the three methods could be done with no syntax at all, just pointing and clicking While there are a number of reasons you WANT to do the syntax, including saving it as a record, because it is easier to make changes, I am not one of those people who sneers at pointing and clicking your way through an analysis. I think that is a perfectly fine way to get used to new procedures. However, if you do that, I strongly recommend you copy and paste your syntax

Propensity Scores, Quintiles Step Task SPSS commands 1 Create propensity scores Logistic Regression (dependent = CITY) Analyze > Regression > Logistic 2 Create quintiles Frequencies Analyze > Descriptive >Frequencies Transform > Recode into different variables 3 Match quintiles Select If Use Complex Samples 4 Conduct analysis Logistic regression with OUTCOME as dependent

Propensity Scores, Matching Step Task SPSS commands 1 Create propensity scores Logistic Regression (dependent = CITY) Analyze > Regression > Logistic 2 Create Dataset1 Select and Save Dataset1 Records Data > Select Cases >If File > Save (select variables) 3 Create Dataset2

PSM Continued Step Task SPSS commands Data > Sort Cases 4 Sort dataset1 Data > Sort Cases 5 Sort dataset2 Select and Save Dataset1 Records Data > Select Cases >If File > Save (select variables) Merge files

And that … … is the general idea There are many options, not nearly all of which we will cover in the next few days, but now you have the general idea

It would help if you already knew this A little about regression Something about SPSS syntax But, if not, oh well .