. use "C:\Users\Ken\Dropbox\WP.DOC\Jews\APSA2012\apsa1.dta", clear

. *following commands generate factor score called polact

. factor polact1-polact12, mineigen(1)

(obs=4558)

Factor analysis/correlation Number of obs = 4558

Method: principal factors Retained factors = 1

Rotation: (unrotated) Number of params = 12

--------------------------------------------------------------------------

Factor | Eigenvalue Difference Proportion Cumulative

-------------+------------------------------------------------------------

Factor1 | 3.18825 2.82780 1.0551 1.0551

Factor2 | 0.36045 0.14691 0.1193 1.1744

Factor3 | 0.21354 0.06551 0.0707 1.2451

Factor4 | 0.14803 0.16188 0.0490 1.2941

Factor5 | -0.01385 0.03371 -0.0046 1.2895

Factor6 | -0.04756 0.01979 -0.0157 1.2738

Factor7 | -0.06735 0.03088 -0.0223 1.2515

Factor8 | -0.09823 0.02922 -0.0325 1.2190

Factor9 | -0.12745 0.03644 -0.0422 1.1768

Factor10 | -0.16390 0.00949 -0.0542 1.1225

Factor11 | -0.17339 0.02350 -0.0574 1.0652

Factor12 | -0.19688 . -0.0652 1.0000

--------------------------------------------------------------------------

LR test: independent vs. saturated: chi2(66) = 1.1e+04 Prob>chi2 = 0.0000

Factor loadings (pattern matrix) and unique variances

---------------------------------------

Variable | Factor1 | Uniqueness

-------------+----------+--------------

polact1 | 0.5381 | 0.7104

polact2 | 0.5984 | 0.6420

polact3 | 0.5701 | 0.6750

polact4 | 0.3049 | 0.9070

polact5 | 0.6255 | 0.6087

polact6 | 0.6210 | 0.6144

polact7 | 0.4681 | 0.7808

polact8 | 0.4837 | 0.7661

polact9 | 0.4535 | 0.7943

polact10 | 0.5569 | 0.6899

polact11 | 0.4386 | 0.8076

polact12 | 0.4296 | 0.8155

---------------------------------------

. rotate

Factor analysis/correlation Number of obs = 4558

Method: principal factors Retained factors = 1

Rotation: orthogonal varimax (Kaiser off) Number of params = 12

--------------------------------------------------------------------------

Factor | Variance Difference Proportion Cumulative

-------------+------------------------------------------------------------

Factor1 | 3.18825 . 1.0551 1.0551

--------------------------------------------------------------------------

LR test: independent vs. saturated: chi2(66) = 1.1e+04 Prob>chi2 = 0.0000

Rotated factor loadings (pattern matrix) and unique variances

---------------------------------------

Variable | Factor1 | Uniqueness

-------------+----------+--------------

polact1 | 0.5381 | 0.7104

polact2 | 0.5984 | 0.6420

polact3 | 0.5701 | 0.6750

polact4 | 0.3049 | 0.9070

polact5 | 0.6255 | 0.6087

polact6 | 0.6210 | 0.6144

polact7 | 0.4681 | 0.7808

polact8 | 0.4837 | 0.7661

polact9 | 0.4535 | 0.7943

polact10 | 0.5569 | 0.6899

polact11 | 0.4386 | 0.8076

polact12 | 0.4296 | 0.8155

---------------------------------------

Factor rotation matrix

-----------------------

| Factor1

-------------+---------

Factor1 | 1.0000

-----------------------

. predict polact, regression

Scoring coefficients (method = regression; based on varimax rotated factors)

------------------------

Variable | Factor1

-------------+----------

polact1 | 0.13694

polact2 | 0.16470

polact3 | 0.14650

polact4 | 0.06245

polact5 | 0.17616

polact6 | 0.17637

polact7 | 0.11175

polact8 | 0.11604

polact9 | 0.10566

polact10 | 0.14622

polact11 | 0.09997

polact12 | 0.09370

------------------------

. alpha polact1-polact12

Test scale = mean(unstandardized items)

Average interitem covariance: .0148708

Number of items in the scale: 12

Scale reliability coefficient: 0.7906

. *following commands generate count variable called polacttot

. generate polacttot=polact1+polact2+polact3+polact4+polact5+polact6+polact7+polact8+polact9+

polact10+polact11+polact12