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Mar 16, 2012 6:11 PM
(3873 views)

Hi,

I'm fitting a model to my data, and I want to see the p values for LSMEANS. I can't figure out how to do this. In SAS, the code would be "LSMEANS /pdiff"

Here is the code from SAS:

proc GLM;

class marker1 marker2 marker3;

model trait = marker1 marker2 marker3 marker1*marker2;

LSMEANS marker1*marker2 / stderr pdiff;

Thanks for any help!

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Mar 17, 2012 5:10 PM
(5492 views)

I do not think that you can directly get the column of p-values in that table. However if you position the mouse pointer in that table and right click you can choose the upper and lower confidence limit items which are 95% limits by default. If you want a different confidence level, rerun the fit model and in the dialog click the red triangle next to Model Specification and choose Set Alpha Level as appropriate.

6 REPLIES

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Mar 17, 2012 9:33 AM
(3035 views)

See if this script sample gives you what you want. It can also be generated interactively through the Fit Model dialog followed by clicking on items under various red triangle pull down menus.

dt = Open( "$SAMPLE_DATA/Analgesics.jmp" );

fm = dt << Fit Model(

Y( :pain ),

Effects( :gender, :drug, :gender * :drug ),

Personality( Standard Least Squares ),

Emphasis( Effect Leverage ),

Run(

:pain << {Lack of Fit( 0 ), Plot Actual by Predicted( 1 ), Plot Regression( 0 ),

Plot Residual by Predicted( 1 ), Plot Effect Leverage( 1 ), {:gender <<

{LSMeans Student's t( 0.05, Ordered Differences Report( 1 ) )}, :drug <<

{LSMeans Student's t( 0.05, Ordered Differences Report( 1 ) )}, :gender * :drug <<

{LSMeans Student's t( 0.05, Ordered Differences Report( 1 ) )}}}

),

SendToReport(

Dispatch(

{"Response pain", "Whole Model", "Parameter Estimates"},

"Lower 95%",

NumberColBox,

{Hide( 0 )}

),

Dispatch(

{"Response pain", "Whole Model", "Parameter Estimates"},

"Upper 95%",

NumberColBox,

{Hide( 0 )}

),

Dispatch(

{"Response pain", "gender", "Least Squares Means Table"},

"Lower 95%",

NumberColBox,

{Hide( 0 )}

),

Dispatch(

{"Response pain", "gender", "Least Squares Means Table"},

"Upper 95%",

NumberColBox,

{Hide( 0 )}

),

Dispatch(

{"Response pain", "drug", "Least Squares Means Table"},

"Lower 95%",

NumberColBox,

{Hide( 0 )}

),

Dispatch(

{"Response pain", "drug", "Least Squares Means Table"},

"Upper 95%",

NumberColBox,

{Hide( 0 )}

),

Dispatch(

{"Response pain", "gender*drug", "Least Squares Means Table"},

"Lower 95%",

NumberColBox,

{Hide( 0 )}

),

Dispatch(

{"Response pain", "gender*drug", "Least Squares Means Table"},

"Upper 95%",

NumberColBox,

{Hide( 0 )}

)

)

);

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Mar 17, 2012 9:38 AM
(3035 views)

Thanks - actually what I was looking for was the equivalent options under the red triangles - can you tell me what I need to click on to get similar output to SAS?

Thanks!

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Mar 17, 2012 9:44 AM
(3035 views)

For example,

1. Under the red triangle for gender*drug click LSMeans Student's t

2. Under the red triangle for LSMeans Differences Student's t click Ordered Differences Report

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Mar 17, 2012 10:04 AM
(3035 views)

ok, this is really close! What I want is the Least Squares Means Table (which I can get in JMP), but with a column for the p values? Is this possible?

I know the p values are in the ordered list, but it is hard to find the right comparisons and SAS outputs the table nicely, like this:

The GLM Procedure

LeastSquares Means

maysin Standard LSMEAN

p1 umc105 LSMEAN Error Pr > |t| Number

A A 0.40225326 0.03832313 <.0001 1

A B 0.94394072 0.03824324 <.0001 2

A H 0.48262441 0.02545524 <.0001 3

B A -0.05712529 0.05182397 0.2714 4

B B 0.09619548 0.04285878 0.0257 5

B H 0.03895248 0.02771541 0.1611 6

H A 0.16287842 0.02784603 <.0001 7

H B 0.48242779 0.03588362 <.0001 8

H H 0.25725291 0.02200943 <.0001 9

JMP can give almost the same table, but it doesn't have the p values:

Level | Least Sq Mean | Std Error |

A,A | 0.40225326 | 0.03832313 |

A,B | 0.94394072 | 0.03824324 |

A,H | 0.48262441 | 0.02545524 |

B,A | -0.05712529 | 0.05182397 |

B,B | 0.09619548 | 0.04285878 |

B,H | 0.03895248 | 0.02771541 |

H,A | 0.16287842 | 0.02784603 |

H,B | 0.48242779 | 0.03588362 |

H,H | 0.25725291 | 0.02200943 |

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Mar 17, 2012 5:10 PM
(5493 views)

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Mar 18, 2012 9:56 AM
(3035 views)

Cool, thanks. Actually confidence intervals make more sense in this situation than p values anyways, so this works great! I had no idea you could add columns by right clicking... I wonder what other tables have hidden columns!