ЗДЕСЬ ПРО МЕТОД, КОТОРЫМ ОН ВЫБИРАЛ КОЛИЧЕСТВО ФАКТОРОВ
## Parallel analysis suggests that the number of factors = 4 and the number of components = 4
The suggested number of factors is 4, so we will start with a model with 4 factors.
ЗДЕСЬ РИСУНОЧЕК
ЗДЕСЬ НУЖНО СРЕДИ СТОЛБЦОМ MR1, MR2, MR3, MR4 ПОСМОТРЕТЬ, ГДЕ САМОЕ БОЛЬШОЕ ЧИСЛО (ПО МОДУЛЮ) И ПОДПИСАТЬ СЕБЕ СТРЕЛОЧКИ В КАРТИНКЕ ЭТИМ САМЫМ БОЛЬШИМ ЧИСЛОМ. ИЗ КАКОГО СТОЛБЦА ЧИСЛО, К ТОМУ И ПРИНАДЛЕЖИТ ФАКТОР
## Factor Analysis using method = minres
## Call: fa(r = dataf1, nfactors = 4)
## Standardized loadings (pattern matrix) based upon correlation matrix
## MR1 MR2 MR3 MR4 h2 u2 com
## scl_somatization 0.68 -0.39 -0.13 -0.09 0.637 0.363 1.7
## scl_sensitive 0.84 -0.02 0.10 0.20 0.816 0.184 1.1
## scl_vrajdebno 0.82 0.01 0.15 -0.10 0.747 0.253 1.1
## scl_phobia 0.76 0.16 -0.01 -0.01 0.576 0.424 1.1
## scl_paranoyaln 0.70 0.31 0.09 0.08 0.592 0.408 1.4
## scl_psychotism 0.84 0.07 -0.01 0.23 0.771 0.229 1.2
## scl_gsi 0.96 0.04 0.00 -0.01 0.911 0.089 1.0
## scl_psdi 0.89 -0.03 -0.09 -0.16 0.779 0.221 1.1
## glo1_soc_odobr 0.13 0.54 0.43 0.04 0.449 0.551 2.1
## glo2_dominant -0.06 0.06 -0.05 0.10 0.021 0.979 2.9
## glo3_control 0.38 0.18 -0.03 -0.46 0.355 0.645 2.3
## glo4_pr_nastr 0.48 -0.50 -0.03 0.02 0.512 0.488 2.0
## glo5_openness 0.37 0.01 0.22 0.38 0.370 0.630 2.6
## glo6_soc_ability 0.31 -0.05 -0.37 0.53 0.485 0.515 2.5
## SACS_assertive 0.00 0.21 0.21 -0.65 0.496 0.504 1.4
## SACS_soc_control 0.03 0.17 0.20 0.71 0.575 0.425 1.3
## SACS_soc_support 0.03 0.13 0.11 0.59 0.380 0.620 1.2
## SACS_careful_actions -0.26 -0.09 0.24 0.46 0.305 0.695 2.3
## SACS_avoidance -0.36 -0.28 0.53 0.15 0.440 0.560 2.6
## SACS_manipulative_actions 0.03 -0.08 0.66 0.25 0.523 0.477 1.3
## SACS_asocial_actions -0.01 0.10 0.54 -0.01 0.282 0.718 1.1
## need_material 0.21 0.07 0.39 -0.18 0.254 0.746 2.1
## need_safety -0.23 0.16 0.65 -0.03 0.422 0.578 1.4
## need_mejlich_soc 0.11 0.21 -0.60 0.25 0.487 0.513 1.7
## need_priznanie 0.32 0.08 0.66 -0.25 0.661 0.339 1.8
## need_self_expression -0.09 -0.12 -0.54 -0.21 0.365 0.635 1.5
## scale_s -0.18 0.82 -0.06 0.02 0.743 0.257 1.1
## scale_1 -0.06 0.59 -0.26 -0.27 0.531 0.469 1.8
## scale_2 -0.55 0.44 0.01 0.19 0.568 0.432 2.2
## scale_3 0.05 0.75 -0.22 0.28 0.723 0.277 1.5
## scale_4 0.12 0.80 -0.01 0.04 0.641 0.359 1.0
## cum_1 0.09 0.79 0.24 -0.22 0.690 0.310 1.4
## cum_2 0.05 0.15 -0.20 0.52 0.345 0.655 1.5
## cum_3 -0.41 0.45 -0.11 0.05 0.453 0.547 2.1
## cum_4 -0.04 -0.12 -0.15 0.39 0.190 0.810 1.5
## cum_6 0.23 0.64 -0.08 0.06 0.454 0.546 1.3
## cum_7 -0.49 0.37 -0.25 -0.03 0.546 0.454 2.4
## perc_vytesnenie 0.11 0.18 0.09 0.13 0.068 0.932 3.1
## perc_compensation 0.10 -0.38 0.36 0.32 0.440 0.560 3.1
## perc_projection 0.38 -0.26 0.57 0.04 0.685 0.315 2.2
## perc_substitution 0.48 -0.14 0.53 0.01 0.652 0.348 2.1
##
## MR1 MR2 MR3 MR4
## SS loadings 7.78 5.30 4.50 3.36
## Proportion Var 0.19 0.13 0.11 0.08
## Cumulative Var 0.19 0.32 0.43 0.51
## Proportion Explained 0.37 0.25 0.21 0.16
## Cumulative Proportion 0.37 0.62 0.84 1.00
##
## With factor correlations of
## MR1 MR2 MR3 MR4
## MR1 1.00 -0.09 0.20 0.04
## MR2 -0.09 1.00 -0.11 0.02
## MR3 0.20 -0.11 1.00 -0.01
## MR4 0.04 0.02 -0.01 1.00
##
## Mean item complexity = 1.8
## Test of the hypothesis that 4 factors are sufficient.
##
## The degrees of freedom for the null model are 820 and the objective function was 352.71 with Chi Square of 4056.13
## The degrees of freedom for the model are 662 and the objective function was 330.13
##
## The root mean square of the residuals (RMSR) is 0.1
## The df corrected root mean square of the residuals is 0.11
##
## The harmonic number of observations is 27 with the empirical chi square 418.69 with prob < 1
## The total number of observations was 27 with Likelihood Chi Square = 2916.14 with prob < 3e-279
##
## Tucker Lewis Index of factoring reliability = -0.216
## RMSEA index = 0.353 and the 90 % confidence intervals are 0.349 0.375
## BIC = 734.29
## Fit based upon off diagonal values = 0.88
| scl navyazchivost | scl anxiety | scl depression | SACS impulsive actions | SACS aggressive actions | Index constructivity | cum 5 | perc rejection | perc regress | perc intelligence | perc reaction reversed | |||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Predictors | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p | Estimates | CI | p |
| (Intercept) | 0.49 | -0.17 – 1.16 | 0.136 | 0.99 | -0.07 – 2.04 | 0.067 | 0.43 | -0.23 – 1.09 | 0.189 | 19.97 | 13.32 – 26.63 | <0.001 | 21.69 | 14.48 – 28.90 | <0.001 | 1.22 | 0.88 – 1.57 | <0.001 | 72.23 | 40.04 – 104.43 | <0.001 | 110.06 | 67.12 – 153.01 | <0.001 | 67.28 | 19.07 – 115.48 | 0.009 | 65.47 | 14.39 – 116.54 | 0.015 | 91.27 | 43.96 – 138.57 | 0.001 |
| MR1 | 0.31 | 0.16 – 0.47 | <0.001 | 0.67 | 0.43 – 0.91 | <0.001 | 0.45 | 0.30 – 0.60 | <0.001 | 0.30 | -1.23 – 1.83 | 0.681 | 1.18 | -0.48 – 2.83 | 0.154 | 0.02 | -0.06 – 0.10 | 0.567 | 12.40 | 5.00 – 19.81 | 0.002 | -2.48 | -12.36 – 7.39 | 0.603 | 15.54 | 4.46 – 26.62 | 0.009 | -0.71 | -12.45 – 11.03 | 0.900 | -2.95 | -13.82 – 7.93 | 0.576 |
| MR2 | -0.16 | -0.31 – -0.01 | 0.038 | -0.10 | -0.33 – 0.14 | 0.407 | -0.00 | -0.15 – 0.15 | 0.997 | 0.03 | -1.45 – 1.51 | 0.965 | -0.89 | -2.50 – 0.72 | 0.261 | 0.07 | -0.01 – 0.14 | 0.082 | -4.89 | -12.07 – 2.29 | 0.170 | 2.58 | -6.99 – 12.16 | 0.578 | -11.56 | -22.31 – -0.81 | 0.037 | 4.60 | -6.79 – 15.99 | 0.407 | -7.68 | -18.23 – 2.87 | 0.143 |
| MR3 | -0.06 | -0.20 – 0.07 | 0.347 | -0.02 | -0.24 – 0.21 | 0.884 | -0.00 | -0.14 – 0.14 | 0.983 | 1.13 | -0.26 – 2.52 | 0.104 | 1.22 | -0.28 – 2.73 | 0.105 | -0.08 | -0.16 – -0.01 | 0.023 | 1.86 | -4.87 – 8.58 | 0.569 | 3.84 | -5.13 – 12.81 | 0.381 | 3.79 | -6.28 – 13.86 | 0.439 | 8.17 | -2.50 – 18.83 | 0.125 | -0.06 | -9.94 – 9.82 | 0.989 |
| MR4 | 0.20 | 0.06 – 0.34 | 0.008 | 0.01 | -0.22 – 0.24 | 0.934 | -0.00 | -0.14 – 0.14 | 0.955 | 1.18 | -0.24 – 2.60 | 0.098 | 1.50 | -0.04 – 3.04 | 0.056 | 0.03 | -0.04 – 0.10 | 0.392 | -2.67 | -9.54 – 4.20 | 0.424 | 11.35 | 2.19 – 20.51 | 0.018 | 0.23 | -10.05 – 10.52 | 0.962 | 3.05 | -7.85 – 13.95 | 0.564 | 10.70 | 0.61 – 20.79 | 0.039 |
| age | 0.02 | -0.03 – 0.07 | 0.412 | -0.00 | -0.08 – 0.07 | 0.900 | 0.05 | -0.00 – 0.10 | 0.052 | 0.00 | -0.49 – 0.49 | 0.997 | -0.26 | -0.80 – 0.27 | 0.311 | 0.01 | -0.02 – 0.03 | 0.490 | -1.01 | -3.40 – 1.37 | 0.385 | -1.83 | -5.01 – 1.35 | 0.242 | -0.48 | -4.05 – 3.09 | 0.780 | -0.76 | -4.54 – 3.02 | 0.678 | -0.84 | -4.35 – 2.66 | 0.621 |
| time [До года] | 0.11 | -0.29 – 0.51 | 0.555 | -0.13 | -0.76 – 0.51 | 0.683 | 0.02 | -0.38 – 0.41 | 0.923 | -1.29 | -5.30 – 2.71 | 0.506 | -3.04 | -7.38 – 1.31 | 0.159 | 0.05 | -0.16 – 0.26 | 0.619 | -28.14 | -47.52 – -8.75 | 0.007 | -13.47 | -39.32 – 12.38 | 0.288 | 11.47 | -17.55 – 40.49 | 0.417 | 20.44 | -10.31 – 51.18 | 0.180 | -2.43 | -30.90 – 26.05 | 0.860 |
| time [До двух лет] | 0.42 | -0.19 – 1.03 | 0.168 | 0.10 | -0.87 – 1.07 | 0.831 | 0.08 | -0.53 – 0.68 | 0.793 | -1.77 | -7.87 – 4.34 | 0.551 | 0.37 | -6.25 – 6.99 | 0.908 | -0.16 | -0.47 – 0.15 | 0.296 | -47.57 | -77.13 – -18.01 | 0.003 | -7.99 | -47.42 – 31.44 | 0.675 | 30.27 | -13.99 – 74.54 | 0.168 | 4.76 | -42.14 – 51.65 | 0.834 | -13.98 | -57.41 – 29.45 | 0.508 |
| Observations | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | ||||||||||||||||||||||
| R2 / R2 adjusted | 0.729 / 0.624 | 0.742 / 0.641 | 0.832 / 0.767 | 0.312 / 0.045 | 0.482 / 0.281 | 0.496 / 0.301 | 0.737 / 0.635 | 0.364 / 0.117 | 0.547 / 0.371 | 0.324 / 0.061 | 0.354 / 0.103 | ||||||||||||||||||||||
ЗДЕСЬ СМОТРЕТЬ НА ЗНАЧИМЫЕ ПО P И МОЖНО ПОСМОТРЕТЬ НА ЗНАЧЕНИЯ R2