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| Original file line number | Diff line number | Diff line change |
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| version 10 | ||
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| cap program drop pls | ||
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| program pls, rclass byable(recall) | ||
| syntax anything(id="Indicator blocks" name=blocks equalok) [if] [in] , /// | ||
| Adjacent(string) /// | ||
| [ ModeB(namelist) /// | ||
| Scheme(string)] | ||
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| /* Parse the specified blocks. | ||
| * Macros: | ||
| * C`i' - composite name | ||
| * i`i' - indicators for composite, by composite index | ||
| * i`C`i'' - indicators for composite, by composite name | ||
| * allindicators - all indicators | ||
| * allcomposites - all composites | ||
| */ | ||
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| tokenize `"`blocks'"', parse(" ()=") | ||
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| scalar inblock = 0 | ||
| scalar startblock = 0 | ||
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| // Count of composites | ||
| local j 0 | ||
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| while "`1'"~=""{ | ||
| if "`1'"=="(" { | ||
| if inblock{ | ||
| di as error "Unexpected (" | ||
| error 197 | ||
| } | ||
| scalar inblock = 1 | ||
| scalar startblock = 1 | ||
| local ++j | ||
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| } | ||
| else if inblock{ | ||
| if "`1'"==")" { | ||
| if("C`j'"=="" || "i`j'"==""){ | ||
| di as error "Incomplete block specification" | ||
| error 197 | ||
| } | ||
| else{ | ||
| scalar inblock = 0 | ||
| local i`C`j'' `i`j'' | ||
| local allindicators "`allindicators' `i`j''" | ||
| local allcomposites "`allcomposites' `C`j''" | ||
| } | ||
| } | ||
| else if "`1'"=="=" { | ||
| scalar startblock = 0 | ||
| } | ||
| else if startblock { | ||
| if "`C`j''" ~= ""{ | ||
| di as error "Missing =" | ||
| error 197 | ||
| } | ||
| confirm new variable `1' | ||
| else local C`j' `1' | ||
| } | ||
| else{ | ||
| confirm variable `1' | ||
| else local i`j' "`i`j'' `1'" | ||
| } | ||
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| } | ||
| else error 197 | ||
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| macro shift | ||
| } | ||
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| if inblock{ | ||
| di as error "Missing )" | ||
| error 197 | ||
| } | ||
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| /* End of parsing the blocks */ | ||
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| /* Parse the inner weight scheme */ | ||
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| if "`scheme'" == "" local scheme "centroid" | ||
| if ! ("`scheme'" == "centroid" || "`scheme'" == "factor" || "`scheme'" == "path"){ | ||
| di as error "scheme must be either centroid, factor, or path" | ||
| error 198 | ||
| } | ||
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| /* Set obs to use */ | ||
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| marksample touse, novarlist | ||
| markout `touse'`allindicators' | ||
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| quietly count if `touse' | ||
| if r(N) == 0 error 2000 | ||
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| /* Initialize composites with equal weights */ | ||
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| foreach i of numlist 1/`j'{ | ||
| quietly egen `C`i'' = rowtotal(`i`i'') if `touse' | ||
| quietly center `C`i'', standardize inplace | ||
| } | ||
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| /* Parse adjacencies */ | ||
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| tokenize `"`adjacent'"', parse(",") | ||
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| while "`1'"~=""{ | ||
| local 0 `1' | ||
| syntax varlist(min=2) | ||
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| // Use macros r`var' and c`compositename' to store whether | ||
| // the adjacency is treated as directional in path weighting scheme | ||
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| local dv: word 1 of `varlist' | ||
| local ivs: list varlist - dv | ||
| local r`dv' `r`dv'' `ivs' | ||
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| foreach iv in `ivs'{ | ||
| local c`iv' `c`iv'' `dv' | ||
| } | ||
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| macro shift | ||
| macro shift | ||
| } | ||
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| foreach var in `allcomposites'{ | ||
| if "`r`var''`c`var''"== ""{ | ||
| di as error "Composite `var' is not adjacent to any other composite" | ||
| error 198 | ||
| } | ||
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| if("`scheme'" == "path"){ | ||
| local c`var': list uniq c`var' | ||
| local r`var': list uniq r`var' | ||
| local c`var': list c`var' - r`var' | ||
| } | ||
| else{ | ||
| local c`var' `c`var'' `r`var'' | ||
| local c`var': list uniq c`var' | ||
| local r`var' "" | ||
| } | ||
| } | ||
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| /* Verify Mode B specification and create Mode A specification*/ | ||
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| local 0 `modeB' | ||
| syntax [varlist] | ||
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| local modeA: list allcomposites - modeB | ||
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| /* | ||
| * Start of the PLS weight algorithm | ||
| */ | ||
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| scalar converged = 0 | ||
| scalar iteration = 0 | ||
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| while(!converged){ | ||
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| // Inner estimation. The three commonly used schemes are | ||
| // Centroid: The sign of correlations | ||
| // Factor: The correlations | ||
| // Path: Correlations and regresions | ||
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| // Update the composites as weighted sums of adjacent composites. | ||
| // These are stored as separate temporary variables | ||
| // for computational reasons | ||
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| foreach var in `allcomposites'{ | ||
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| tempvar t`var' | ||
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| // Inner estimation with regression weights (path) | ||
| if("`r`var''"!=""){ | ||
| quietly regress `var' `r`var'' if `touse' | ||
| quietly predict `t`var'' if `touse' | ||
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| } | ||
| else quietly generate `t`var'' = 0 if `touse' | ||
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| // Inner estimation with correlational weights (all schemes) | ||
| foreach var2 in `c`var''{ | ||
| quietly correlate `var' `var2' if `touse' | ||
| matrix define C = r(C) | ||
| if "`scheme'" == "centroid" quietly replace `t`var'' = `t`var'' + `var2' * C[1,1]/abs(C[1,2]) if `touse' | ||
| else quietly replace `t`var'' = `t`var'' + `var2' * C[1,2] if `touse' | ||
| } | ||
| } | ||
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| // Store weights in matrix. These are unscaled and only used for | ||
| // convergence check | ||
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| matrix define W = 0 | ||
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| // Outer estimation (Mode A) | ||
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| foreach var in `modeA'{ | ||
| quietly replace `var' = 0 if `touse' | ||
| foreach var2 in `i`var''{ | ||
| quietly correlate `t`var'' `var2' if `touse' | ||
| matrix define C = r(C) | ||
| matrix define W = W , C[1,2] | ||
| quietly replace `var' = `var' + `var2' * C[1,2] if `touse' | ||
| } | ||
| } | ||
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| // Outer estimation (Mode B) | ||
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| foreach var in `modeB'{ | ||
| tempvar tv | ||
| quietly regress `t`var'' `i`var'' if `touse' | ||
| matrix define W = W , e(b) | ||
| quietly predict `tv' if `touse' | ||
| quietly replace `var' = `tv' if `touse' | ||
| quietly drop `tv' | ||
| } | ||
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| // Clean up | ||
| foreach var in `allcomposites'{ | ||
| quietly drop `t`var'' | ||
| } | ||
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| // Standardize the composites | ||
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| quietly center `allcomposites' if `touse', standardize inplace | ||
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| // Convergence check:compare new weights (W) with the weights from previous | ||
| // iteration (Wold). | ||
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| if(iteration > 0) scalar converged = mreldif(W, Wold) < 0.00001 | ||
| matrix define Wold = W | ||
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| scalar iteration = iteration +1 | ||
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| // No convergence | ||
| if(iteration>1000) error 430 | ||
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| } | ||
| return scalar iterations = iteration | ||
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| end | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,107 @@ | ||
| {smcl} | ||
| {* *! version 1.0 29oct2015}{...} | ||
| {viewerjumpto "Syntax" "pls##syntax"}{...} | ||
| {viewerjumpto "Description" "pls##description"}{...} | ||
| {viewerjumpto "Options" "pls##options"}{...} | ||
| {viewerjumpto "Remarks" "pls##remarks"}{...} | ||
| {viewerjumpto "Examples" "pls##examples"}{...} | ||
| {title:Title} | ||
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| {phang} | ||
| {bf:pls} {hline 2} calculates composite variables using the partial least squares path modeling (PLS) algorithm | ||
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| {marker syntax}{...} | ||
| {title:Syntax} | ||
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| {p 8 14 2} | ||
| {cmd:pls} {cmd:(}{newvar:1} = {varlist:1}{cmd:)} | ||
| {cmd:(}{newvar:2} = {varlist:2}{cmd:)} | ||
| {it:...} {cmd:(}{newvar:N} = {varlist:N}{cmd:)} {ifin} | ||
| [, {it:options}] | ||
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| {synoptset 50 tabbed}{...} | ||
| {synopthdr} | ||
| {synoptline} | ||
| {syntab:Main} | ||
| {synopt:{cmdab:a:djacent(}{varlist:1} [, {varlist:2}, {it:...}, {varlist:N}])}defines which composites are adjacent to each other{p_end} | ||
| {synopt:{opt m:odeB}({varlist})}sets Mode B outer estimation{p_end} | ||
| {synopt:{opt s:cheme(scheme)}}sets innner estimation scheme{p_end} | ||
| {synoptline} | ||
| {p2colreset}{...} | ||
| {p 4 6 2} | ||
| {cmd:by} is allowed; see {manhelp by D}.{p_end} | ||
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| {marker description}{...} | ||
| {title:Description} | ||
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| {pstd} | ||
| {cmd:pls} calculates composite variables using the partial least squares path | ||
| modeling (PLS) algorithm. | ||
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| {pstd} | ||
| The composites are calculated as weighted combinations of existing variables | ||
| using the weight algorithm introduced by Wold (see {help pls##wold1982:Wold (1982)}). | ||
| The produces composites are indentical to the composties produced by commercial | ||
| PLS software as well as the open source | ||
| {browse "https://cran.r-project.org/web/packages/matrixpls/index.html":matrixpls} | ||
| R package except for small numerical differences due to different convergence | ||
| criterion. | ||
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| {marker options}{...} | ||
| {title:Options} | ||
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| {dlgtab:Main} | ||
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| {phang} | ||
| {cmd:adjacent(}{varlist:1} [, {varlist:2}, {it:...}, {varlist:N}]) defines which composites are adjacent to each other during inner | ||
| estimation. The first variable of varlist is defined as being adjacent to the | ||
| other variables. If the path scheme is used for inner estimation, the | ||
| directionality of adjacencies is from the other variables toward the first | ||
| variable. | ||
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| {phang} | ||
| {opt modeB}({varlist})}sets Mode B outer estimation for the composites in varlist. All other composites are calculated with Mode A outer estimation. | ||
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| {phang} | ||
| {opt scheme(scheme)} sets innner estimation scheme. Valid values for scheme are centroid, factor, and path. The default is the centroid method.{p_end} | ||
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| {marker remarks}{...} | ||
| {title:Remarks} | ||
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| {phang} | ||
| This program is provided for educational purposes. It is difficult to recommend | ||
| the PLS composites for any serious empirical work | ||
| (see {help pls##rma2015:Ršnkkš, McIntosh, and Antonakis (2015)}) | ||
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| {marker examples}{...} | ||
| {title:Example} | ||
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| {pstd}Setup{p_end} | ||
| {phang2}{cmd:. webuse sem_sm2}{p_end} | ||
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| {pstd}Calculate PLS composites{p_end} | ||
| {phang2}{cmd:. pls (Alien67 = anomia67 pwless67)}{break} | ||
| {cmd:(Alien71 = anomia71 pwless71)}{break} | ||
| {cmd:(SES = educ66 occstat66),}{break} | ||
| {cmd:adjacent(Alien71 Alien67 SES, Alien67 SES)}{break} | ||
| {cmd:modeB(SES)}{break} | ||
| {cmd:scheme("path")}{break} | ||
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| {pstd}Regression between composites{p_end} | ||
| {phang2}{cmd:. regress Alien67 SES}{p_end} | ||
| {phang2}{cmd:. regress Alien71 Alien67 SES}{p_end} | ||
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| {marker references}{...} | ||
| {title:References} | ||
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| {marker wold1982}{...} | ||
| {phang} | ||
| Wold, H. (1982). Soft modeling: The basic design and some extensions. | ||
| In K. G. Jšreskog & S. Wold (Eds.), {it:Systems under indirect observation?: causality, structure, prediction} (pp. 1Ð54). Amsterdam: North-Holland. | ||
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| {marker rma2015}{...} | ||
| {phang} | ||
| Ršnkkš, M., McIntosh, C. N., & Antonakis, J. (2015). On the adoption of partial least squares in psychological research: Caveat emptor. {it:Personality and Individual Differences}, (87), 76Ð84. | ||
| {browse "http://doi.org/10.1016/j.paid.2015.07.019":DOI:10.1016/j.paid.2015.07.019} | ||
| {p_end} |