LMATRIX, MMATRIX, and KMATRIX Subcommands (GLM command)
- The L matrix is called the contrast coefficients matrix. This matrix specifies coefficients of contrasts, which can be used
for studying the between-subjects effects in the model. One way to
define the L matrix is by specifying the
CONTRAST
subcommand, on which you select a type of contrast. Another way is to specify your own L matrix directly by using theLMATRIX
subcommand. See the topic LMATRIX Subcommand (GLM: Univariate command) for more information. - The M matrix is called the transformation coefficients
matrix. This matrix provides a transformation for the dependent
variables. This transformation can be used to construct contrasts
among the dependent variables in the model. The M matrix can
be specified on the
MMATRIX
subcommand. See the topic MMATRIX Subcommand (GLM: Multivariate command) for more information. - The K matrix is called the contrast results matrix. This matrix specifies the results matrix in the general linear
hypothesis. To define your own K matrix, use the
KMATRIX
subcommand. See the topic KMATRIX Subcommand (GLM: Univariate command) for more information.
For univariate and multivariate models, you can specify one, two, or all three of the L, M, and K matrices. If only one or two types are specified, the unspecified matrices use the defaults that are shown in the following table (read across the rows).
L matrix | M matrix | K matrix |
---|---|---|
If LMATRIX is used
to specify the L matrix |
Default = identity matrix* | Default = zero matrix |
Default = intercept matrix† | If MMATRIX is used
to specify the M matrix |
Default = zero matrix |
Default = intercept matrix† | Default = identity matrix* | If KMATRIX is used to specify
the K matrix |
* The dimension of the identity matrix is the same as the number of dependent variables that are being studied.
† The intercept matrix is the matrix that corresponds to the estimable function for the intercept term in the model, provided that the intercept term is included in the model. If the intercept term is not included in the model, the L matrix is not defined, and this custom hypothesis test cannot be performed.
Example
GLM Y1 Y2 BY A B
/LMATRIX = A 1 -1
/DESIGN A B.
Assume that factor A has two levels.
- Because there are two dependent variables, this model is a multivariate model with two main factor effects, A and B.
- A custom hypothesis test is requested by the
LMATRIX
subcommand. - Because no
MMATRIX
orKMATRIX
is specified, the M matrix is the default two-dimensional identity matrix, and the K matrix is a zero-row vector (0, 0).
For a repeated measures model, you can specify one, two, or all three of the L, M, and K matrices. If only one or two types are specified, the unspecified matrices use the defaults that are shown in the following table (read across the rows).
L matrix | M matrix | K matrix |
---|---|---|
If LMATRIX is used
to specify the L matrix |
Default = average matrix* | Default = zero matrix |
Default = intercept matrix† | If MMATRIX is used
to specify the M matrix |
Default = zero matrix |
Default = intercept matrix† | Default = average matrix* | If KMATRIX is used to specify
the K matrix |
* The average matrix is the transformation matrix that corresponds to the transformation for the between-subjects test. The dimension is the number of measures.
† The intercept matrix is the matrix that corresponds to the estimable function for the intercept term in the model, provided that the intercept term is included in the model. If the intercept term is not included in the model, the L matrix is not defined, and this custom hypothesis test cannot be performed.
Example
GLM Y1 Y2 BY A B
/WSFACTOR TIME (2)
/MMATRIX Y1 1 Y2 1; Y1 1 Y2 -1
/DESIGN A B.
- Because
WSFACTOR
is specified, this model is a repeated measures model with two between-subjects factors A and B, and a within-subjects factor, TIME. - A custom hypothesis is requested by the
MMATRIX
subcommand. The M matrix is a 2 x 2 matrix:1 1 1 -1
- Because the L matrix and K matrix are not specified, their defaults are used. The default for the L matrix is the matrix that corresponds to the estimable function for the intercept term in the between-subjects model, and the default for the K matrix is a zero-row vector (0, 0).