求問!我的LISREL跑不出圖來 ><”

我用LISREL跑我的模式

.OUT檔有出來 可是圖卻沒有出來

(就是適配度的分析結果有出來 可是卻沒有圖

檔案裡面沒有.PHI的檔 ><")

OUT檔裡面有出現這兩句話

W_A_R_N_I_N_G: PHI is not positive definite

W_A_R_N_I_N_G: PSI is not positive definite

想請問各位大大

這樣我是哪裡有錯誤呢!?

步驟和程式語言應該是沒有錯 找過同學來對過

他們可以跑出來 我卻不行 ><"

拜託各位幫忙了

小弟感激不盡!!

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    模型非正定。請從新對參數進行重新的設定!

    您好會出現的這問題主要有四種原因(喬治亞州立大學Edward E. Rigdon教授所提出的論點)

    1.First, the researcher may get a message saying that the input covariance or correlation matrix being analyzed is "not positive definite." Generalized least squares (GLS) estimation requires that the covariance or correlation matrix analyzed must be positive definite, and maximum likelihood (ML) estimation will also perform poorly in such situations. If the matrix to be analyzed is found to be not positive definite, many programs will simply issue an error message and quit.

    2.Second, the message may refer to the asymptotic covariance matrix. This is not the covariance matrix being analyzed, but rather a weight matrix to be used with asymptotically distribution-free / weighted least squares (ADF/WLS) estimation.

    3.Third, the researcher may get a message saying that its estimate of Sigma (), the model-implied covariance matrix, is not positive definite. LISREL, for example, will simply quit if it issues this message.

    4.Fourth, the program may indicate that some parameter matrix within the model is not positive definite. This attribute is only relevant to parameter matrices that are variance/covariance matrices. In the language of the LISREL program, these include the matrices Theta-delta, Theta-epsilon, Phi () and Psi. Here, however, this "error message" can result from correct specification of the model, so the only problem is convincing the program to stop worrying about it.

    @@@Why is My Matrix Not Positive Definite, and What Can I Do About It?@@@

    1.Linear Dependency

    2.Error Reading the Data

    3.Typographical Error

    4.Starting Values

    5.Sampling Variation

    6.Missing Data

    7.My Variable is a Constant!

    8.Polychoric Correlations

    9.No Error Variance

    10.No Error Variance

    11.Negative Error Variance

    Source(s): http://www2.gsu.edu/ 以及 個人代跑的經驗
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