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Posted 04-30-2018 11:54 AM
(1864 views)

I am running a regularized regression on several traits using the following code:

Proc glmselect data = DalReg1 plots(stepaxis=normb)=coefficients;

Model TW = Protein TGW SGD GL GW Size Shape / selection = LASSO(stop=none choose = cvex);

run;

The output is great. However, I am wondering how to obtain standard errors for each coefficient. Help suggestions on this, please?

Thanks,

Dalitso

8 REPLIES 8

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Ballardw: Here is the output. There is no SE.

SAS Output

Analysis of Variance Source DF Sum of Squares Mean Square F Value Model Error Corrected Total

5 | 4523.88515 | 904.77703 | 208.11 |

1271 | 5525.89163 | 4.34767 | |

1276 | 10050 |

Root MSE Dependent Mean R-Square Adj R-Sq AICAI CCS BC CVEX PRESS

2.08511 |

58.92247 |

0.4501 |

0.4480 |

3161.71694 |

3161.80520 |

1913.63055 |

4.85730 |

Parameter Estimates Parameter DF Estimate Intercept Protein TGW SGD GL Shape

1 | 19.141464 |

1 | -0.221838 |

1 | 0.192900 |

1 | 15.111831 |

1 | 0.040392 |

1 | 0.195827 |

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There are no SE provided when variable selection is performed with LASSO. There might be a good reason for that. Models resulting from variable selection methods do not account in their parameter estimates SE for model uncertainty. You can get parameter SEs for the chosen model, conditional on that choice, with other regression procedures, such as GLM, GENMOD or GLIMMIX.

PG

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You might consider doing LASSO selection via PROC NLMIXED instead as illustrated in this note.

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Hi Dave,

I am not sure if I am familiar with NLMIXED. Is there any other way with proc GLMSELECT? If not I might just to have a go at NLMIXED and see.

Thanks Dave.

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`proc hpgenselect data=sashelp.class ;`

class sex;

model weight = sex height age/ **CL** ;

selection method=Lasso(choose=SBC) details=all;

performance details;

run;

You will see :

```
NOTE: The CL option is not available for the LASSO method.
NOTE: The HPGENSELECT procedure is executing in single-machine mode.
NOTE: * Optimal Value of Criterion
NOTE: There were 19 observations read from the data set SASHELP.CLASS.
```

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Ksharp,

This is what I have seen:

NOTE: The CL option is not available for the LASSO method.

NOTE: The HPGENSELECT procedure is executing in single-machine mode.

NOTE: * Optimal Value of Criterion

NOTE: There were 1496 observations read from the data set WORK.DALREG1.

NOTE: PROCEDURE HPGENSELECT used (Total process time):

real time 1.07 seconds

cpu time 0.51 seconds

I just read about Bayesian LASSO that has the ability to generate SE. However, it requires a macro, an area I am, sadly, not competent with. Any help from anybody please?

Thanks,

DNY

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