{smcl}
{hline}
help for {cmd:factortest}{right:Joao Pedro Azevedo}
{hline}
{title:Calculate specification tests before {cmd:factor} or {cmd:pca}}
{p 8 27}{cmdab:factortest}
[{it:varlist}]
[{cmd:if} {it:exp}]
[{cmd:in} {it:range}]
{title:Description}
{p 4 4 2}{cmd:factortest} performs the {hi:Bartlett's test for sphericity} and
the {hi:Kaiser-Meyer-Olkin Measure of Sampling Adequacy}. Both tests should be used
prior to a factor or a principal component analysis.{p_end}
{title:Technical details}
{p 4 4 2}{bf:Determinant of the matrix of correlation}: This determinant will equal 1.0
only if all correlations equal 0, otherwise the determinant will be less than 1.{p_end}
{p 4 4 2}{bf:Bartlett's test for sphericity}: Calculates the determinant of the matrix of
the sums of products and cross-products (S) from which the intercorrelations
matrix is derived. The determinant of the matrix S is converted to a chi-square
statistic and tested for significance.{p_end}
{p 4 4 2}The null hypothesis is that the intercorrelation matrix comes from a population
in which the variables are noncollinear (i.e. an identity matrix), and that the
non-zero correlations in the sample matrix are due to sampling error.{p_end}
{p 4 4 2}{bf:Kaiser-Meyer-Olkin Measure of Sampling Adequacy}: is an index for comparing the
magnitudes of the observed correlation coefficients to the magnitudes of the
partial correlation coefficients.{p_end}
{p 4 4 2}Large values for the KMO measure indicate that a factor analysis of the variables
is a good idea. {p_end}
{p 32 0 0}90 or above, excelent{p_end}
{p 32 0 0}80 or above, meritorious{p_end}
{p 32 0 0}70 or above, middling{p_end}
{p 32 0 0}60 or above, mediocre{p_end}
{p 32 0 0}50 or above, miserable; and{p_end}
{p 32 0 0}below .50, unacceptable.{p_end}
{title:Examples}
{p 8 12 2}{cmd:. factortest price mpg rep78 rep77 hdroom rseat trunk}
{title:References}
{p 4 8 2}Box,G.E.P.(1949) "A general distribution theory for a class of likelihood
criteria." {it:Biometrica}, 36: 317-346.
{p 4 8 2}Cureton, E.E., & D'Agostino, R.B. (1983). Factor analysis: An applied
approach. Hillsdale, NJ: Erlbaum.
{title:Authors}
Joao Pedro Azevedo, IPEA, Brazil
jazevedo@ipea.gov.br
{title:Aknowledgements}
{p 4 8 2}I would like to thank May M. Boggess for her help and Roberto De Miguel for his suggestions.
{title:Also see}
{p 4 13 2}Manual: {hi:[R] factor} {hi:[R] pca} {hi:[R] alpha}{p_end}
{p 4 13 2}Online: help for {help factor}; {help pca}; {help alpha} {p_end}