2

統合識別改善 (IDI) について、2 つの非常に異なる結果が得られています。

nriidi.pkg パッケージを使用して実行するidiと、この出力が得られます

    . idi totaloutcome grace_prob, prvars(allelecount)

----------------------------------------------------
      IDI |     Estimate     Std. Err.       P-value
 ----------+-----------------------------------------
           |     -0.01116       0.00430       0.00946
 ----------------------------------------------------

しかし、idiMark Lunt のプログラムから

 . net from http://personalpages.manchester.ac.uk/staff/mark.lunt

 . idi totaloutcome allelecount grace_prob

 Integrated Discrimination Improvement for allelecount = 0.0017
 Standard Error                                        = 0.0022
 z                                                     = 0.7615
 P-value (one-sided)                                   = 0.2232
 P-value (two-sided)                                   = 0.4464

なぜこれが発生するのか、またはあるパッケージが他のパッケージよりも優れている理由を説明できる人はいますか?

4

2 に答える 2

1

どちらも同じ答えを返します。たとえば、cancerStata のデータを使用した以下を参照してください。

sysuse cancer

ペントidiコマンドの場合:

Syntax

        idi outcomevar new_marker varlist [if] [in]


The command idi calculates the Integrated Discrimination Improvement (IDI) due to
    a new marker new_marker, where the old model predicted outcomevar from varlist.
    The definition of the IDI is given by Pencina et al (2008). It can be thought of
    as the average improvement in sensitivity across all possible cutoffs.

idi died drug age

Integrated Discrimination Improvement for drug = 0.2044
Standard Error                                 = 0.0575
z                                              = 3.5554
P-value (one-sided)                            = 0.0002
P-value (two-sided)                            = 0.0004

上記の例では、新しいマーカーは薬であるため、おそらくそれによる改善をテストしています:

Bybergidiからの場合:

Syntax

    idi depvar varlist1 [, options]


    options                  description
    ----------------------------------------------------------------------------------
    Main

      prvars(varlist2)        variable list of new predictor variables

 prvars() is not optional; see below.


Description

    idi calculates the integrated discrimination improvement, which is, as is nri, a
    measure that compares the discrimination ability between two logistic regression
    prediction models. The command assumes a binary numerical depvar and two sets of
    numerical and/or categorical covariates for the two models. The xi function is not
    yet available and dummy variables for categorical covariates with more than two
    categories need to be specified by the user.
    Output are estimated IDI with standard error and p value for test of the null
    hypothesis that IDI in the population is zero.
    Also see: nri

.

idi died age, prvars(drug)

----------------------------------------------------
      IDI |     Estimate     Std. Err.       P-value
----------+-----------------------------------------
          |      0.20436       0.05748       0.00038
----------------------------------------------------

ここで、新しいマーカーは次のとおりですprvars。

于 2013-08-08T18:36:30.590 に答える