Ergebnisse

Structural Equation Modelling

Models Info
   
Estimation MethodDWLS.
Optimization MethodNLMINB 
Number of observations298 
Free parameters66 
Standard errorsStandard 
Scaled testMean adjusted scaled and shifted 
ConvergedTRUE 
Iterations382 
   
Modelgroup=~GruppeA_B 
  Glaubwuerdigkeit=~Exp_1+Exp_2+Exp_3+Vert_1+Vert_2+Vert_3 
  Kaufabsicht=~Kauf_1+Kauf_2+Kauf_3 
  EinstellungWerbung=~EW_1+EW_2+EW_3+EW_4+EW_5 
  EinstellungMarke=~EM_1+EM_2+EM_3+EM_4+EM_5 
  Glaubwuerdigkeit~group 
 Kaufabsicht~Glaubwuerdigkeit+group 
 EinstellungWerbung~Glaubwuerdigkeit+group 
 EinstellungMarke~Glaubwuerdigkeit+group 
   
Note. Variable (GruppeA_B) has been coerced to ordered type.
[3] [4]

 

Overall Tests

Model tests
Labeldfp
User Model84.01631.000
Baseline Model7290.2190< .001
Scaled User295.0163< .001
Scaled Baseline1321.9190< .001

 

Fit indices
95% Confidence Intervals
TypeSRMRRMSEALowerUpperRMSEA p
Classical0.0400.0000.0000.0001.000
Robust0.039    
Scaled0.0390.0520.0430.0620.340

 

User model versus baseline model
 ModelScaled
Comparative Fit Index (CFI)1.0000.883
Tucker-Lewis Index (TLI)1.0130.864
Bentler-Bonett Non-normed Fit Index (NNFI)1.0130.864
Relative Noncentrality Index (RNI)1.0110.883
Bentler-Bonett Normed Fit Index (NFI)0.9880.777
Bollen's Relative Fit Index (RFI)0.9870.740
Bollen's Incremental Fit Index (IFI)1.0110.886
Parsimony Normed Fit Index (PNFI)0.8480.666

 

Additional fit indices
 Model
Hoelter Critical N (CN), α=0.05686.486
Hoelter Critical N (CN), α=0.01736.457
Goodness of Fit Index (GFI)0.999
Adjusted Goodness of Fit Index (AGFI)0.998
Parsimony Goodness of Fit Index (PGFI)0.711
McDonald Fit Index (MFI)1.142
Expected Cross-Validation Index (ECVI).
Loglikelihood user model (H0).
Loglikelihood unrestricted model (H1).
Akaike (AIC).
Bayesian (BIC).
Sample-size adjusted Bayesian (SABIC).

 

Estimates

Parameters estimates
95% Confidence Intervalsβ 95% Confidence Intervals
LabelDepPredEstimateSELowerUpperβLowerUpperzp
p21Glaubwuerdigkeitgroup-3.140.695-4.51-1.78-0.975-1.12-0.835-4.520< .001
p22KaufabsichtGlaubwuerdigkeit-2.495.151-12.597.60-1.377-6.954.200-0.4840.629
p23Kaufabsichtgroup-11.3314.637-40.0217.36-1.944-7.383.496-0.7740.439
p24EinstellungWerbungGlaubwuerdigkeit-6.7111.369-28.9915.57-3.311-14.297.671-0.5900.555
p25EinstellungWerbunggroup-24.9832.306-88.3038.33-3.826-14.546.888-0.7730.439
p26EinstellungMarkeGlaubwuerdigkeit-5.559.708-24.5813.47-3.056-13.527.405-0.5720.567
p27EinstellungMarkegroup-21.3527.587-75.4232.72-3.646-13.856.559-0.7740.439

 

Measurement model
95% Confidence Intervalsβ 95% Confidence Intervals
LabelLatentObservedEstimateSELowerUpperβLowerUpperzp
p1groupGruppeA_B1.0000.00001.0001.0000.1480.07490.220  
p2GlaubwuerdigkeitExp_11.0000.00001.0001.0000.5320.46530.599  
p3 Exp_21.1990.07971.0431.3550.6300.55600.70315.0< .001
p4 Exp_31.1990.07871.0441.3530.6420.56930.71515.2< .001
p5 Vert_11.4090.09251.2281.5900.7100.62860.79115.2< .001
p6 Vert_21.2430.08061.0851.4010.6780.60240.75415.4< .001
p7 Vert_31.3600.08771.1881.5320.7590.67300.84515.5< .001
p8KaufabsichtKauf_11.0000.00001.0001.0000.8620.75830.966  
p9 Kauf_21.2360.06591.1071.3660.9420.81951.06518.8< .001
p10 Kauf_31.1700.06421.0441.2950.8790.75701.00118.2< .001
p11EinstellungWerbungEW_11.0000.00001.0001.0000.8590.75150.966  
p12 EW_20.8670.04500.7780.9550.8180.71850.91819.3< .001
p13 EW_30.8640.04510.7750.9520.8000.70240.89819.1< .001
p14 EW_40.8140.04290.7300.8980.7710.67740.86619.0< .001
p15 EW_50.8830.04590.7930.9730.7880.69170.88419.2< .001
p16EinstellungMarkeEM_11.0000.00001.0001.0000.8410.74220.941  
p17 EM_20.9230.04490.8351.0110.8280.73590.91920.5< .001
p18 EM_30.9200.04490.8321.0080.8190.72920.90920.5< .001
p19 EM_40.8800.04300.7960.9650.8080.71810.89820.5< .001
p20 EM_50.9040.04410.8180.9910.8350.73930.93120.5< .001

 

Variances and Covariances
95% Confidence Intervalsβ 95% Confidence Intervals
LabelVariable 1Variable 2EstimateSELowerUpperβLowerUpperzp
p29GruppeA_BGruppeA_B0.97820.00000.97820.97820.97820.95681.000  
p30Exp_1Exp_10.57210.06840.43800.70630.71670.64540.7888.359< .001
p31Exp_2Exp_20.49520.07110.35590.63460.60360.51110.6966.967< .001
p32Exp_3Exp_30.46280.06690.33170.59390.58750.49380.6816.920< .001
p33Vert_1Vert_10.44260.08170.28260.60270.49640.38150.6115.419< .001
p34Vert_2Vert_20.41040.06630.28040.54040.54000.43710.6436.186< .001
p35Vert_3Vert_30.30780.06900.17260.44300.42390.29340.5544.463< .001
p36Kauf_1Kauf_10.25610.10720.04600.46610.25700.07820.4362.3890.017
p37Kauf_2Kauf_20.14350.1611-0.17240.45930.1125-0.11840.3430.8900.373
p38Kauf_3Kauf_30.29800.1692-0.03370.62960.22730.01280.4421.7610.078
p39EW_1EW_10.33100.14710.04270.61940.26270.07870.4472.2500.024
p40EW_2EW_20.34460.11510.11890.57020.33060.16730.4942.9920.003
p41EW_3EW_30.38900.11890.15600.62200.35940.20270.5163.2720.001
p42EW_4EW_40.41870.11080.20170.63580.40480.25960.5503.781< .001
p43EW_5EW_50.44330.12660.19520.69150.37960.22850.5313.502< .001
p44EM_1EM_10.30830.11530.08220.53430.29220.12530.4592.6730.008
p45EM_2EM_20.29290.09340.10970.47600.31520.16350.4673.1340.002
p46EM_3EM_30.30940.09340.12640.49230.32870.18110.4763.314< .001
p47EM_4EM_40.30790.08850.13450.48130.34720.20200.4923.480< .001
p48EM_5EM_50.26550.09200.08520.44590.30290.14330.4632.8850.004
p49groupgroup0.02180.01103.17e-40.04321.00001.00001.0001.9890.047
p50GlaubwuerdigkeitGlaubwuerdigkeit0.01100.0315-0.05080.07280.0488-0.22410.3220.3500.727
p51KaufabsichtKaufabsicht0.40420.05600.29450.51390.54610.47390.6187.222< .001
p52EinstellungWerbungEinstellungWerbung0.10240.0783-0.05100.25580.1103-0.05070.2711.3090.191
p53EinstellungMarkeEinstellungMarke0.07680.0565-0.03390.18740.1028-0.04170.2471.3600.174
p54KaufabsichtEinstellungWerbung0.00000.00000.00000.00000.00000.00000.000  
p55KaufabsichtEinstellungMarke0.00000.00000.00000.00000.00000.00000.000  
p56EinstellungWerbungEinstellungMarke0.00000.00000.00000.00000.00000.00000.000  

 

Intercepts
95% Confidence Intervals
LabelVariableInterceptSELowerUpperzp
p58GruppeA_B0.0000.0000.0000.000  
p59Exp_13.3760.0543.2703.48262.553< .001
p60Exp_23.5070.0563.3973.61662.869< .001
p61Exp_33.3390.0543.2333.44561.698< .001
p62Vert_13.3490.0563.2393.45959.688< .001
p63Vert_23.4930.0523.3923.59567.550< .001
p64Vert_33.5200.0503.4223.61870.412< .001
p65Kauf_13.0840.0582.9703.19853.136< .001
p66Kauf_22.9930.0662.8653.12245.652< .001
p67Kauf_33.0370.0682.9033.17044.560< .001
p68EW_13.4430.0683.3093.57750.325< .001
p69EW_23.7450.0663.6163.87456.954< .001
p70EW_33.5030.0633.3803.62755.670< .001
p71EW_43.5300.0623.4083.65256.811< .001
p72EW_53.6480.0693.5133.78352.957< .001
p73EM_13.4830.0623.3613.60555.915< .001
p74EM_23.5740.0583.4603.68861.272< .001
p75EM_33.5100.0593.3953.62659.542< .001
p76EM_43.4700.0563.3613.57962.487< .001
p77EM_53.7110.0573.6003.82365.045< .001
p78group0.0000.0000.0000.000  
p79Glaubwuerdigkeit0.0000.0000.0000.000  
p80Kaufabsicht0.0000.0000.0000.000  
p81EinstellungWerbung0.0000.0000.0000.000  
p82EinstellungMarke0.0000.0000.0000.000  

 

Thresholds
95% Confidence Intervals
LabelVariableStepThresholdsSELowerUpperzp
p28GruppeA_Bt1-0.0080.073-0.1510.134-0.1160.908

 

Defined parameters
95% Confidence Intervalsβ 95% Confidence Intervals
LabelDescriptionParameterEstimateSELowerUpperβLowerUpperzp
IE1group ⇒ Glaubwuerdigkeit ⇒ Kaufabsichtp21*p227.82815.641-22.82838.4831.343-4.296.970.5000.617
IE2group ⇒ Glaubwuerdigkeit ⇒ EinstellungWerbungp21*p2421.09334.299-46.13288.3173.230-7.9414.400.6150.539
IE3group ⇒ Glaubwuerdigkeit ⇒ EinstellungMarkep21*p2617.45429.321-40.01374.9222.981-7.6513.610.5950.552

 

Path Model

Path diagrams

[5]

Structural Equation Models

Models Info
   
Estimation MethodDWLS.
Optimization MethodNLMINB 
Number of observations298 
Free parameters67 
Standard errorsStandard 
Scaled testNone 
ConvergedFALSE 
Iterations51 
   
ModelGlaubwuerdigkeit=~Exp_1+Exp_2+Exp_3+Vert_1+Vert_2+Vert_3 
 Kaufabsicht=~Kauf_1+Kauf_2+Kauf_3 
 EinstellungWerbung=~EW_1+EW_2+EW_3+EW_4+EW_5 
 EinstellungMarke=~EM_1+EM_2+EM_3+EM_4+EM_5 
 Glaubwuerdigkeit~GruppeA_B 
 Kaufabsicht~Glaubwuerdigkeit+GruppeA_B 
 EinstellungWerbung~Glaubwuerdigkeit+GruppeA_B 
 EinstellungMarke~EinstellungWerbung+GruppeA_B 
   
Note. Variable (GruppeA_B) has been coerced to ordered type.
Note. lavaan WARNING: estimator “DWLS” is not recommended for continuous data. Did you forget to set the ordered= argument?
Note. longer object length is not a multiple of shorter object length
Note. Additional warnings are present.
[3] [4]

 

Overall Tests

Model tests
Labeldfp
User Model...
Baseline Model...
Note. The model cannot be estimated, please refine it. Reason: : fit measures not available if model did not converge

 

Fit indices
95% Confidence Intervals
SRMRRMSEALowerUpperRMSEA p
.....
Note. The model cannot be estimated, please refine it. Reason: : fit measures not available if model did not converge

 

User model versus baseline model
 Model
Comparative Fit Index (CFI).
Tucker-Lewis Index (TLI).
Bentler-Bonett Non-normed Fit Index (NNFI).
Relative Noncentrality Index (RNI).
Bentler-Bonett Normed Fit Index (NFI).
Bollen's Relative Fit Index (RFI).
Bollen's Incremental Fit Index (IFI).
Parsimony Normed Fit Index (PNFI).
Note. The model cannot be estimated, please refine it. Reason: : fit measures not available if model did not converge

 

Estimates

Parameters estimates
95% Confidence Intervals
DepPredEstimateSELowerUpperβzp
GlaubwuerdigkeitGruppeA_B1.171      
KaufabsichtGlaubwuerdigkeit0.584   0.559  
KaufabsichtGruppeA_B0.294      
EinstellungWerbungGlaubwuerdigkeit0.926   0.663  
EinstellungWerbungGruppeA_B0.649      
EinstellungMarkeEinstellungWerbung0.752   0.781  
EinstellungMarkeGruppeA_B0.479      
Note. longer object length is not a multiple of shorter object length
Note. lavaan WARNING: Could not compute standard errors! The information matrix could not be inverted. This may be a symptom that the model is not identified.

 

Measurement model
95% Confidence Intervals
LatentObservedEstimateSELowerUpperβzp
GlaubwuerdigkeitExp_11.0000.001.001.000.662  
 Exp_20.420   0.377  
 Exp_30.477   0.412  
 Vert_10.399   0.373  
 Vert_20.548   0.450  
 Vert_30.367   0.358  
KaufabsichtKauf_11.0000.001.001.000.731  
 Kauf_20.697   0.515  
 Kauf_30.660   0.498  
EinstellungWerbungEW_11.0000.001.001.000.780  
 EW_20.747   0.658  
 EW_30.716   0.646  
 EW_40.739   0.655  
 EW_50.704   0.645  
EinstellungMarkeEM_11.0000.001.001.000.771  
 EM_20.700   0.629  
 EM_30.672   0.619  
 EM_40.686   0.627  
 EM_50.265   0.314  

 

Variances and Covariances
95% Confidence Intervals
Variable 1Variable 2EstimateSELowerUpperβzp
Exp_1Exp_10.834   0.561  
Exp_2Exp_20.692   0.858  
Exp_3Exp_30.725   0.830  
Vert_1Vert_10.641   0.861  
Vert_2Vert_20.770   0.797  
Vert_3Vert_30.599   0.872  
Kauf_1Kauf_10.617   0.465  
Kauf_2Kauf_20.956   0.735  
Kauf_3Kauf_30.936   0.752  
EW_1EW_10.819   0.392  
EW_2EW_20.925   0.567  
EW_3EW_30.910   0.583  
EW_4EW_40.924   0.571  
EW_5EW_50.882   0.583  
EM_1EM_10.804   0.406  
EM_2EM_20.881   0.604  
EM_3EM_30.855   0.616  
EM_4EM_40.858   0.607  
EM_5EM_50.755   0.902  
GlaubwuerdigkeitGlaubwuerdigkeit0.651   1.000  
KaufabsichtKaufabsicht0.488   0.687  
EinstellungWerbungEinstellungWerbung0.711   0.560  
EinstellungMarkeEinstellungMarke0.460   0.391  
KaufabsichtEinstellungMarke0.391   0.825  
GruppeA_BGruppeA_B-7.53e−16   1.000  

 

Intercepts
95% Confidence Intervals
VariableInterceptSELowerUpperzp
Exp_1-0.933     
Exp_2-0.932     
Exp_3-0.935     
Vert_1-0.881     
Vert_2-1.060     
Vert_3-1.141     
Kauf_1-0.751     
Kauf_2-0.587     
Kauf_3-0.554     
EW_1-0.609     
EW_2-0.724     
EW_3-0.734     
EW_4-0.756     
EW_5-0.647     
EM_1-0.734     
EM_2-0.862     
EM_3-0.831     
EM_4-0.915     
EM_5-0.948     
GruppeA_B-1.614     
Glaubwuerdigkeit0.0000.0000.0000.000  
Kaufabsicht0.0000.0000.0000.000  
EinstellungWerbung0.0000.0000.0000.000  
EinstellungMarke0.0000.0000.0000.000  

 

Descriptives

Descriptives
 GruppeA_B
N298
Missing0
Mean1.50
Median2.00
Standard deviation0.501
Minimum1
Maximum2

 

Frequencies

Frequencies of GruppeA_B
GruppeA_BCounts% of TotalCumulative %
Gruppe_provokant14849.7 %49.7 %
Gruppe_nichtprovokant15050.3 %100.0 %

 

References

[1] The jamovi project (2024). jamovi. (Version 2.5) [Computer Software]. Retrieved from https://www.jamovi.org.

[2] R Core Team (2023). R: A Language and environment for statistical computing. (Version 4.3) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2024-01-09).

[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] 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.