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Posted 09-08-2020 05:32 PM
(530 views)

Hi all,

I would like to perform a Spearman correlation on the scores from a single variable in my dataset. I have six other variables that categorize all participants into 6 different groups by giving them a 1 or a 0.

How can I use proc corr to say that I want to calculate the correlation coefficient on the scores for each different group as defined by the 6 other variables? An example table of what I am hoping for is below.

Group 1 | Group 2 | Group 3 | Group 4 | Group 5 | Group 6 | |

Group 1 | Correlation coefficient for score on test | |||||

Group 2 | ||||||

Group 3 | ||||||

Group 4 | ||||||

Group 5 | ||||||

Group 6 |

5 REPLIES 5

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Please show us a portion of the original data

--

Paige Miller

Paige Miller

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Here is part of my dataset with the variables of interest.

Obs Score group1 group2 group3 group4 group5 group612345678

71.00 | 1 | . | . | 1 | . | . |

20.00 | . | . | . | . | . | 1 |

29.00 | . | . | . | . | . | 1 |

44.00 | . | 1 | . | 1 | . | . |

20.00 | . | 1 | . | 1 | . | . |

63.00 | 1 | . | . | 1 | . | . |

50.00 | . | 1 | . | . | . | . |

62.00 | . | 1 | . | 1 | . | 1 |

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Here is the dataset with no formatting errors.

Score | Group1 | Group2 | Group3 | Group4 | Group5 | Group6 |

71.00 | 1 | . | . | 1 | . | . |

20.00 | . | . | . | . | . | 1 |

29.00 | . | . | . | . | . | 1 |

44.00 | . | 1 | . | 1 | . | . |

20.00 | . | 1 | . | 1 | . | . |

63.00 | 1 | . | . | 1 | . | . |

50.00 | . | 1 | . | . | . | . |

62.00 | . | 1 | . | 1 | . | 1 |

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I have to admit I don't understand. A Spearman correlation cannot be calculated if the only values in the data are 1 or missing. Even if (as you said in your original message, but not in your most recent messge) that the values are 1 and 0, I don't see this as a candidate for a Spearman correlation. Correlation between two binary variables is measured by the Phi Coefficient, which is an output from PROC FREQ.

I'm also mystified by your title, "how to denote different categories", which doesn't seem to relate at all to anything you have written.

--

Paige Miller

Paige Miller

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