{smcl} {hline} {title:Optifact - v1.2 - 11 Mar 2008} {hi:Find the most appropriate summated rating scales from a list of items} {title:Syntax} {p 8 17 2} {cmd:optifact} {varlist} {ifin} {weight} [{cmd:,} {it:options}] {title:Options} {p 4 8 2}{cmd:top(#)} The number of the best candidate scales to list after analysis (default 10) {p 4 8 2}{cmd:smallest(#)} The smallest number of items allowed in the candidate scales (default 3) {p 4 8 2}{cmd:largest(#)} The largest number of items allowed in the candidate scales (default is all the items) {p 4 8 2}{cmd:maxfact(#)} The maximum number of factors (latent concepts) in the scale (default is 1) {p 4 8 2}{cmd:minslope(#)} The minimum allowable slope in the canonical correlation model (default .01) {p 4 8 2}{cmd:criteria(varlist)} A list of variables for criterion validity testing using canonical correlation {p 4 8 2}{cmd:type(string)} The type of factor analysis to use. Must be one of pf pcf or ml. Default is pf. See help for {help factor} {p 4 8 2}{cmd:sig} Output the statistical significance of the model (assumes ml models). Note this is the probability from the factor model (with ml option) that all parameters of the model are zero in the population. {break}To get the statistical significance of alpha, {help bootstrap} the particular scale you are interested in. {break}For example: bootstrap "factor item1 tem2 tem4 item6" r(alpha), reps(400) {p 4 6 2}{cmd:by} may be used with {cmd:optifact}; see {help by}. {p 4 6 2}{cmd:aweights and fweights} are allowed; see {help weight}. {p 4 6 2}{cmd:Note: you must first install {it:matsort} before you can use optifact} {title:Description} {p 4 6 2}{cmd:optifact} examines every possible combination of items specified by {varlist} then lists out the scales with highest alpha and the given number of factors that can be constructed from these items. {title:Example} {p 4 6 2}{cmd:. sysuse} auto {p 4 6 2}{cmd:. optifact} price mpg rep78 headroom trunk weight length turn displacement gear_ratio, largest(4) criteria(foreign) {title:Author} Paul Millar www.ucalgary.ca/~pemillar pemillar@ucalgary.ca