Object Reference : Object View and Procedure Reference : Factor
Save estimated factor score series in the workfile
factor_name.makescores(options) [output_list] [@ observed_list]
The optional output_list describes the factors that you wish to save. There are two formats for the list:
You may specify output_list using a list of integers and/or vectors containing integers identifying the factors that you wish to save (e.g., “1 2 3 5”).
EViews will construct the output series names using the factor names previously specified in the factor object (using Factor::factnames) or using the default names “F1”, “F2”, etc. If a name modifier is provided (using the “append=” option), it will be appended to each name
You may provide an output_list containing names for factors to be saved (e.g., “math science verbal”).
If you provide factor names, EViews will save the first factors to the workfile. The factors will be named using the specified list, appended with the name modifiers, if specified.
By default, EViews will save all of the factors using the names in the factor object, with modifiers if necessary.
The optional observed_list of observed input variables will be multiplied by the score coefficients to compute the scores. Note that:
If an observed_list is not provided, EViews will use the observed variables from factor estimation. For user-specified factor models (specified by providing a symmetric matrix) you must provide a list if you wish to obtain score values.
Scores values will be computed for the current workfile sample. Observations with input values that are missing will generate NAs.
Use unrotated loadings in computations (the default is to use the rotated loadings, if available).
type =arg (default=“exact”)
Exact coefficient (“exact”), coarse adjusted factor coefficients (“coefs”), coarse adjusted factor loadings (“loadings”).
coef=arg (default=“reg”)
Method for computing the factor score coefficient matrix: Thurstone regression (“reg”), Ideal Variables (“ideal”), Bartlett weighted least squares (“wls”), generalized Anderson-Rubin-McDonald (“anderson”), Green (“green”).
For “type=exact” and “type=coefs” specifications.
coarse=arg (default=“unrestrict”)
Method for computing the coarse (-1, 0, 1) scores coefficients (Grice, 1991a):
Unrestricted -- (“unrestrict”) coef weights set based only on sign; Unique–recode (“recode”) only element with highest value is coded to a non-zero value; Unique–drop (“drop”) only elements with loadings not in excess of the threshold are set to non-zero values.
For “type=coefs” and “type=loadings” specifications.
cutoff=number (default = 0.3)
Cutoff value for coarse score coefficient calculation (Grice, 1991a).
For “type=coef” specifications, the cutoff value represents the fraction of the largest absolute coefficient weight per factor against which the absolute exact score coefficients should be compared.
For “type=loadings”, and “type=struct” specifications, the cutoff is the value against which the absolute loadings or structure coefficients should be compared.
moment=arg (default =“est”; if feasible)
Standardize the observables data using means and variances from: original estimation (“est”), or the computed moments from specified observable variables (“obs”).
The “moment=est” option is only available for factor models estimated using Pearson or uncentered Pearson correlation and covariances since the remaining models involve unobserved or non-comparable moments.
Degrees-of-freedom correct the observables variances computed when “moment=obs” (divide sums-of-squares by instead of ).
(Optional) Name of group object to contain the factor score series.
(Optional) Name of matrix in which to save the factor score coefficient matrix.
Force the dialog to appear from within a program.
f1.makescores(coef=green, n=outgrp)
computes factor scores coefficients using Green’s method, then saves the results into series in the workfile using the names in the factor object. The observed data from the estimation specification will be used as inputs to the procedure. If no names have been specified, the names will be “F1”, “F2”, etc. The output series will be saved in the group object OUTGRP.
f1.makescores(coef=green, n=outgrp) 1 2
computes scores in the same fashion, but only saves factors 1 and 2.
f1.makescores(type=coefs) sc1 sc2 sc3
computes coarse factor scores using the default (Thurstone) scores coefficients and saves them in the series SC1, SC2, and SC3. The observed data from the estimation specification will be used as inputs.
See “Estimating Scores” and “Scoring”. See also Factor::scores.