Results

描述

描述
 sexgraoccdephome
N300300300300300
Missing00000
Mean1.372.833.961.842.71
Median1.003.004.002.003.00
Standard deviation0.4830.9531.520.5661.18
Minimum11111
Maximum25635

 

频数

sex频数
sex计数合计%累计%
119063.3 %63.3 %
211036.7 %100.0 %

 

gra频数
gra计数合计%累计%
1103.3 %3.3 %
211839.3 %42.7 %
310133.7 %76.3 %
45418.0 %94.3 %
5175.7 %100.0 %

 

occ频数
occ计数合计%累计%
13010.0 %10.0 %
23010.0 %20.0 %
33411.3 %31.3 %
48127.0 %58.3 %
57725.7 %84.0 %
64816.0 %100.0 %

 

dep频数
dep计数合计%累计%
17525.0 %25.0 %
219765.7 %90.7 %
3289.3 %100.0 %

 

home频数
home计数合计%累计%
16220.7 %20.7 %
26421.3 %42.0 %
38829.3 %71.3 %
47123.7 %95.0 %
5155.0 %100.0 %

 

绘图

sex

gra

occ

dep

home

Descriptives

Descriptives
SkewnessKurtosisShapiro-Wilk
 MeanSDSkewnessSEKurtosisSEWp
STD4.130.529-0.2670.141-0.5770.2810.952< .001
EVA3.990.593-0.6580.1411.8530.2810.950< .001
TEA4.010.609-0.8570.1412.4910.2810.933< .001
PRO3.940.520-0.4870.1411.0950.2810.948< .001
ENV3.900.592-0.5120.1411.5960.2810.957< .001

 

Structural Equation Modelling

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Models Info
   
Estimation MethodML.
Optimization MethodNLMINB 
Number of observations300 
Free parameters14 
Standard errorsStandard 
Scaled testNone 
ConvergedTRUE 
Iterations2 
   
ModelSKL~EVA+PRO+ENV 
 PRO~STD 
 ENV~TEA 
   
[3] [4]

 

Overall Tests

Model tests
Labeldfp
User Model2067< .001
Baseline Model69312< .001

 

Fit indices
95% Confidence Intervals
SRMRRMSEALowerUpperRMSEA p
0.1680.3080.2720.345< .001

 

User model versus baseline model
 Model
Comparative Fit Index (CFI)0.708
Tucker-Lewis Index (TLI)0.499
Bentler-Bonett Non-normed Fit Index (NNFI)0.499
Relative Noncentrality Index (RNI)0.708
Bentler-Bonett Normed Fit Index (NFI)0.703
Bollen's Relative Fit Index (RFI)0.490
Bollen's Incremental Fit Index (IFI)0.710
Parsimony Normed Fit Index (PNFI)0.410

 

Variable
SKL0.458
PRO0.297
ENV0.398
ENV.
STD.
TEA.

 

Estimates

Parameters estimates
DepPredEstimateSEβzp
SKLEVA0.1580.04250.1833.72< .001
SKLPRO0.2390.04470.2425.35< .001
SKLENV0.4000.04100.4629.75< .001
PROSTD0.5360.04760.54511.26< .001
ENVTEA0.6130.04360.63114.08< .001

 

Variances and Covariances
Variable 1Variable 2EstimateSEβzp
SKLSKL0.1420.01160.54212.25< .001
PROPRO0.1890.01550.70312.25< .001
ENVENV0.2110.01720.60212.25< .001
EVAEVA0.3510.02861.00012.25< .001
EVASTD0.1940.02120.6209.13< .001
EVATEA0.2490.02530.6909.84< .001
STDSTD0.2790.02281.00012.25< .001
STDTEA0.2020.02190.6299.23< .001
TEATEA0.3700.03021.00012.25< .001

 

Defined parameters
LabelDescriptionParameterEstimateSEβzp
IE1STD ⇒ PRO ⇒ SKLp4*p20.1280.0260.1324.829< .001
IE2TEA ⇒ ENV ⇒ SKLp5*p30.2450.0310.2918.016< .001

 

Additional outputs

Mardia's coefficients
 Coefficientzχ²dfp
Skewness7.81 39056< .001
Kurtosis71.2720.6  < .001
[5]

 

Path Model

Path diagrams

[6]

描述

描述
 
个案数
缺失
均值
中位数
标准差
最小值
最大值

 

描述

描述
 
个案数
缺失
均值
中位数
标准差
最小值
最大值

 

Structural Equation Models

unable to load shared object '/Applications/jamovi.app/Contents/Resources/modules/jmv/R/data.table/libs/data_table.so': dlopen(/Applications/jamovi.app/Contents/Resources/modules/jmv/R/data.table/libs/data_table.so, 0x0006): Library not loaded: '/Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libR.dylib' Referenced from: '/Applications/jamovi.app/Contents/Resources/modules/jmv/R/data.table/libs/data_table.so' Reason: tried: '/Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libR.dylib' (no such file), '/usr/lib/libR.dylib' (no such file)

Models Info
   
Estimation MethodML.
Optimization MethodNLMINB 
Number of observations300 
Free parameters22 
Standard errorsStandard 
Scaled testNone 
ConvergedTRUE 
Iterations67 
   
ModelSKL~STD+PRO+EVA+TEA+ENV 
 PRO~STD 
 ENV~TEA 
   
[3] [4]

 

Overall Tests

Model tests
Labeldfp
User Model2055< .001
Baseline Model69312< .001

 

Fit indices
95% Confidence Intervals
SRMRRMSEALowerUpperRMSEA p
0.1470.3660.3240.409< .001

 

User model versus baseline model
 Model
Comparative Fit Index (CFI)0.706
Tucker-Lewis Index (TLI)0.293
Bentler-Bonett Non-normed Fit Index (NNFI)0.293
Relative Noncentrality Index (RNI)0.706
Bentler-Bonett Normed Fit Index (NFI)0.703
Bollen's Relative Fit Index (RFI)0.288
Bollen's Incremental Fit Index (IFI)0.709
Parsimony Normed Fit Index (PNFI)0.293

 

Additional fit indices
 Model
Hoelter Critical N (CN), α=0.0517.169
Hoelter Critical N (CN), α=0.0123.034
Goodness of Fit Index (GFI)0.995
Adjusted Goodness of Fit Index (AGFI)0.973
Parsimony Goodness of Fit Index (PGFI)0.184
McDonald Fit Index (MFI)0.716
Expected Cross-Validation Index (ECVI)0.831
Loglikelihood user model (H0)-1089.834
Loglikelihood unrestricted model (H1)-987.130
Akaike (AIC)2223.668
Bayesian (BIC)2305.151
Sample-size adjusted Bayesian (SABIC)2235.380

 

Variable
SKL0.463
PRO0.297
ENV0.398
EVA.
TEA.
ENV.

 

Estimates

Parameters estimates
DepPredEstimateSEβzp
SKLSTD0.02540.06210.02610.4080.683
SKLPRO0.22580.04990.22824.524< .001
SKLEVA0.13830.05370.15932.5730.010
SKLTEA0.02190.06030.02590.3630.716
SKLENV0.39420.04740.45378.323< .001
PROSTD0.53570.04760.545011.258< .001
ENVTEA0.61330.04360.630814.081< .001

 

Variances and Covariances
Variable 1Variable 2EstimateSEβzp
SKLSKL0.1420.01160.53712.25< .001
PROPRO0.1890.01550.70312.25< .001
ENVENV0.2110.01720.60212.25< .001
STDSTD0.2790.02281.00012.25< .001
STDEVA0.1940.02120.6209.13< .001
STDTEA0.2020.02190.6299.23< .001
EVAEVA0.3510.02861.00012.25< .001
EVATEA0.2490.02530.6909.84< .001
TEATEA0.3700.03021.00012.25< .001

 

Intercepts
VariableInterceptSEzp
SKL0.7010.2113.316< .001
PRO1.7250.1988.718< .001
ENV1.4400.1778.147< .001
STD4.1250.030135.285< .001
EVA3.9900.034116.699< .001
TEA4.0130.035114.285< .001

 

Defined parameters
LabelDescriptionParameterEstimateSEβzp
IE1STD ⇒ PRO ⇒ SKLp6*p20.1210.0290.1244.198< .001
IE2TEA ⇒ ENV ⇒ SKLp7*p50.2420.0340.2867.165< .001

 

Additional outputs

Heterotrait-monotrait (HTMT) ratio of correlations
 
.
.
注释. HTMT indices not available for this model.
[5]

 

Mardia's coefficients
 Coefficientzχ²dfp
Skewness7.81 39056< .001
Kurtosis71.2720.6  < .001
[5]

 

Path Model

Path diagrams

[6]

参考

[1] The jamovi project (2023). jamovi. (Version 2.4) [Computer Software]. Retrieved from https://www.jamovi.org.

[2] R Core Team (2022). R: A Language and environment for statistical computing. (Version 4.1) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2023-04-07).

[3] Gallucci, M., Jentschke, S. (2021). SEMLj: jamovi SEM Analysis. [jamovi module]. For help please visit https://semlj.github.io/.

[4] Rosseel, Y. (2019). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. link.

[5] Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., Rosseel, Y., Miller, P., Quick, C., Garnier-Villarreal, M., Selig, J., Boulton, A., Preacher, K., Coffman, D., Rhemtulla, M., Robitzsch, A., Enders, C., Arslan, R., Clinton, B., Panko, P., Merkle, E., Chesnut, S., Byrnes, J., Rights, J. D., Longo, Y., Mansolf, M., Ben-Shachar, M. S., Rönkkö, M. (2019). semTools: Useful Tools for Structural Equation Modeling. [R Package]. Retrieved from https://CRAN.R-project.org/package=semTools.

[6] Epskamp S. , Stuber S., Nak J., Veenman M,, Jorgensen T.D. (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. [R Package]. Retrieved from https://CRAN.R-project.org/package=semPlot.