[作业] 求助！HLM软件的操作结果问题 [推广有奖]

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zsw1020647231 发表于 2017-7-3 09:46:04 |AI写论文

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      本人在用HLM进行分析时出现下列结果，请问该怎么处理？

Program:                      HLM 6 Hierarchical Linear and Nonlinear Modeling
Authors:                      Stephen Raudenbush, Tony Bryk, & Richard Congdon
Publisher:                   Scientific Software International, Inc. (c) 2000
                                                   techsupport@ssicentral.com
                                                            www.ssicentral.com
-------------------------------------------------------------------------------
Module:    HLM2R.EXE (6.08.29257.1)
Date:       2 July 2017, Sunday
Time:       1: 2:25
-------------------------------------------------------------------------------

SPECIFICATIONS FOR THIS HLM2 RUN

  Problem Title: no title

  The data source for this run  = new 1
  The command file for this run = C:\Users\majesty\Desktop\成本粘性SAV文件\第二层模型命令.hlm
  Output file name             = C:\Users\majesty\Desktop\成本粘性SAV文件\hlm2.txt
  The maximum number of level-1 units = 3362
  The maximum number of level-2 units = 750
  The maximum number of iterations = 100
  Method of estimation: restricted maximum likelihood

Weighting Specification
-----------------------
                     Weight
                     Variable
         Weighting? Name       Normalized?
Level 1       no
Level 2       no
Precision    no

  The outcome variable is 鈻矻NCOS

  The model specified for the fixed effects was:
----------------------------------------------------

Level-1                Level-2
Coefficients          Predictors
---------------------- ---------------
      INTRCPT1, B0    INTRCPT2, G00
*    YEAR slope, B1    INTRCPT2, G10
* 鈻矻NREV slope, B2    INTRCPT2, G20
* DEC脳鈻?slope, B3    INTRCPT2, G30
                           SIZE, G31
                              MB, G32
                              LEV, G33
                              IOR, G34
                           TEND, G35
                           CASH, G36
                           STOCK, G37
                           TOP1, G38
                              ECB, G39
                              IDP, G310
                              BMN, G311
                              BSN, G312
                              ESR, G313
                              CC, G314
                           NCSKEW, G315

'*' - This level-1 predictor has been centered around its group mean.

The model specified for the covariance components was:
---------------------------------------------------------

      Sigma squared (constant across level-2 units)

      Tau dimensions
            INTRCPT1
               YEAR slope
            鈻矻NREV slope
            DEC脳鈻?slope

Summary of the model specified (in equation format)
---------------------------------------------------

Level-1 Model

Y = B0 + B1*(YEAR) + B2*(鈻矻NREV) + B3*(DEC脳鈻? + R

Level-2 Model
B0 = G00 + U0
B1 = G10 + U1
B2 = G20 + U2
B3 = G30 + G31*(SIZE) + G32*(MB) + G33*(LEV) + G34*(IOR)
      + G35*(TEND) + G36*(CASH) + G37*(STOCK) + G38*(TOP1)
      + G39*(ECB) + G310*(IDP) + G311*(BMN) + G312*(BSN)
      + G313*(ESR) + G314*(CC) + G315*(NCSKEW) + U3
There is a problem in the fixed portion of the model.  A near singularity is
likely.  Possible sources are a collinearity or multicollinearity among the
predictors.  We suggest that you examine a correlation matrix among the fixed
effect predictors.