Fluorite | Level 6

Proc PLS - interpretation of results

Hello, I am running a Proc PLS to find the correlation between my dependent and independent variables, e.g Yield vs MinT MaxT. I am confused as to which  of the tables tells me the percentage of my variables (min T and Max T combined and separately) that explained yield.  My model was fine and below are some of my results.

Please how do I get the percentage of yield explained by a combination of  MinT and MaxT

 The PLS Procedure SC=DRY Percent Variation Accounted for by Partial Least Squares Factors Number of Extracted Factors Model Effects Dependent Variables Current Total Current Total 1 40.0228 40.0228 4.749 4.749 2 59.9772 100 0.0097 4.7587

 SC=DRY Model Effect Loadings Number of Extracted Factors MinT MaxT 1 0.583192 -0.81234 2 0.778905 0.627142 Model Effect Weights Number of Extracted Factors MinT MaxT Inner Regression Coefficients 1 0.628099 -0.78009 0.243576 2 0.778905 0.627142 0.008972 Dependent Variable Weights Number of Extracted Factors Wheat_Y 1 1 2 1

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Diamond | Level 26

Re: Proc PLS - interpretation of results

PLS creates dimensions (sometimes called "factors" or "latent factors") which are used to predict Y. So, dimension 1 (which consists of a weighted combination of both minT and maxT) explains 4.749 percent of the Y variability, and dimension 2 (which consists of a weighted combination of both minT and maxT) explains another 0.0097% of the variability of Y. So I think the answer to your exact question "Please how do I get the percentage of yield explained by a combination of  MinT and MaxT" is given by this number, but you have to decide if you want to use one dimension, or two dimensions.

You can obtain information that a certain percent of the variability of minT is used in dimension 1, and additional percent of variability of minT is used in dimension 2 (same is possible for maxT). You would add the VARSS option to the PROC PLS statement.

https://documentation.sas.com/?cdcId=pgmmvacdc&cdcVersion=9.4&docsetId=statug&docsetTarget=statug_pl...

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Paige Miller
2 REPLIES 2
Diamond | Level 26

Re: Proc PLS - interpretation of results

PLS creates dimensions (sometimes called "factors" or "latent factors") which are used to predict Y. So, dimension 1 (which consists of a weighted combination of both minT and maxT) explains 4.749 percent of the Y variability, and dimension 2 (which consists of a weighted combination of both minT and maxT) explains another 0.0097% of the variability of Y. So I think the answer to your exact question "Please how do I get the percentage of yield explained by a combination of  MinT and MaxT" is given by this number, but you have to decide if you want to use one dimension, or two dimensions.

You can obtain information that a certain percent of the variability of minT is used in dimension 1, and additional percent of variability of minT is used in dimension 2 (same is possible for maxT). You would add the VARSS option to the PROC PLS statement.

https://documentation.sas.com/?cdcId=pgmmvacdc&cdcVersion=9.4&docsetId=statug&docsetTarget=statug_pl...

--
Paige Miller
Fluorite | Level 6

Re: Proc PLS - interpretation of results

Thank you for the response.

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