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I wanted to find out what kind of people (sources) are quoted in articles. To explain, I have done a content analysis of a local newspaper. is there a copy and paste mechanism within the recoding function?
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But now I need to do industrial amounts of recoding and I’m wondering if there’s a way of saving any time/ work – i.e. I am recoding some of my data into different variables – I’ve done a bit of it already and I’ve no problems with the basics. Want to learn more? If you’re just getting started with data analysis in SPSS, or would like a thorough refresher, please join us in our online workshop Introduction to Data Analysis in SPSS. (And of course, once you recode, you should immediately enter value labels and test your syntax to make sure it worked.
SPSS CODE IF SYNTANTX UPDATE
If you don’t have many variables to recode, say one or two, it’s not a big deal to use the menus (but at least paste the code, so you have a record of what you did later!).īut if you have more than just one or two, all those mouse-clicks get old, fast.Īnd if you need to go back and change your coding scheme, say to combine two small categories, it’s a quick matter to update the code. VARIABLE LABELS Educ_cat ‘Education in Categories’. Or, you could do all of that in just a few lines of very logical syntax code: Output variable Label: Education in Categories In it, I am recoding Educ, Years of Education, into 5 categories: Less than High School, High School Grad, Some College, Bachelor’s degree, More than college. This is from the General Social Survey data set that comes along with SPSS.
SPSS CODE IF SYNTANTX HOW TO
Here is an example of how to do it in the menus. So do not recode over an existing variable unless you are absolutely certain that the lost information will never be needed. So if you notice a mistake after you’ve recoded, you can’t fix it.īut you may not even notice the mistake, because you can’t even test it. Recoding Into Same Variables replaces the values in the existing variable. In almost every situation, you want to use Into Different Variables. The command I nto Same Variable replaces existing data with new values, but the command Into Different Variables adds a new variable to the data set. So our goal of the data-analysis is to obtain a point and interval estimate of the slope of the linear trend and the purpose of this contribution is to show how to obtain output that is interpretable as such.SPSS offers two choices under the recode command: I nto Same Variable and Into Different Variables.
SPSS CODE IF SYNTANTX SOFTWARE
That is, standard software (like SPSS) gives us a point estimate and a confidence interval for the contrast estimate, but depending on how the coefficients are scaled, these estimates are not necessarily interpretable in terms of the slope of the linear trend, as I will make clear Maxwell, Delaney, and Kelley (2017) describe how to obtain a confidence interval for the slope and make clear that to obtain interpretable results from the software we use, we should consider how the linear trend contrast values are scaled. The references cited above are clear about how to construct contrast coefficients (lambda coefficients) for linear trends (and non-linear trends for that matter) that can be used to perform a significance test for the null-hypothesis that the slope equals zero. We will use contrast analysis to obtain the relevant data. For linear trend analysis, the relevant effect size is the slope coefficient of the linear trend, so, the purpose of the analysis is to estimate the value of the slope and the 95% confidence interval of the estimate. Here, I will use the frequentist perspective of obtaining a point estimate and a 95% Confidence Interval of the relevant effect size. The estimation perspective to statistical analysis is aimed at obtaining point and interval estimates of effect sizes. I have taken the (invented) data from Haans (2018). The contents of this introduction is based on Maxwell, Delaney, and Kelley (2017) and Rosenthal, Rosnow, and Rubin (2000). The tutorial focuses on obtaining point and confidence intervals.
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This is an introduction to contrast analysis for estimating the linear trend among condition means with R and SPSS.