Results

Descriptives

Descriptives
	Gender
N	307
Missing	4
Mean	1.70
Median	2
Standard deviation	0.459
Minimum	1
Maximum	2

Frequencies

Frequencies of Gender
Gender	Counts	% of Total	Cumulative %
1	92	30.0%	30.0%
2	215	70.0%	100.0%

Structural Equation Models

Models Info

Estimation Method	ML	.
Optimization Method	NLMINB
Number of observations	296
Free parameters	63
Standard errors	Standard
Scaled test	None
Converged	TRUE
Iterations	78
Iterations	78
Model	per_org=~PIF_1+PIF_4+PIF_7
	need_sup=~PIF_2+PIF_5+PIF_8
	dem_abil=~PIF_3+PIF_6+PIF_9
	PIF_3 ~ 1


Multi-group variable	Gender
Note. There are missing values in the data and they are removed listwise. Please consider other methods of handling missing values available in Model Options.
[3] [4]

Overall Tests

Model tests
Label	X²	df	p
User Model	89.5	60	0.008
Baseline Model	1981.0	72	<.001

Constraints score tests
Type	Par 1		Par 2	X²	df	p
Univariate	p2	==	p38	0.1528	1	0.696
	p3	==	p39	0.9404	1	0.332
	p5	==	p41	0.0135	1	0.907
	p6	==	p42	0.0165	1	0.898
	p8	==	p44	0.1410	1	0.707
	p9	==	p45	5.66e-4	1	0.981
	p10	==	p46	3.5293	1	0.060
	p26	==	p62	0.0478	1	0.827
	p27	==	p63	2.0172	1	0.156
	p28	==	p64	2.3026	1	0.129
	p29	==	p65	0.0346	1	0.852
	p30	==	p66	0.8468	1	0.357
	p31	==	p67	0.8089	1	0.368
	p32	==	p68	3.3640	1	0.067
	p33	==	p69	0.0144	1	0.905
Total	p33	==				10.0424	15	0.817

Fit indices
		95% Confidence Intervals
SRMR	RMSEA	Lower	Upper	RMSEA p
0.035	0.058	0.030	0.081	0.292

User model versus baseline model
	Model
Comparative Fit Index (CFI)	0.985
Tucker-Lewis Index (TLI)	0.981
Bentler-Bonett Non-normed Fit Index (NNFI)	0.981
Relative Noncentrality Index (RNI)	0.985
Bentler-Bonett Normed Fit Index (NFI)	0.955
Bollen's Relative Fit Index (RFI)	0.946
Bollen's Incremental Fit Index (IFI)	0.985
Parsimony Normed Fit Index (PNFI)	0.796

Estimates

Measurement model
						95% Confidence Intervals
Group	Label	Latent	Observed	Estimate	SE	Lower	Upper	β	z	p
1	p1	per_org	PIF_1	1.000	0.0000	1.000	1.00	0.717
	p2		PIF_4	1.335	0.1003	1.138	1.53	0.899	13.3	<.001
	p3		PIF_7	1.357	0.0995	1.162	1.55	0.908	13.6	<.001
	p4	need_sup	PIF_2	1.000	0.0000	1.000	1.00	0.859
	p5		PIF_5	1.076	0.0599	0.958	1.19	0.828	18.0	<.001
	p6		PIF_8	1.062	0.0525	0.960	1.17	0.946	20.3	<.001
	p7	dem_abil	PIF_3	1.000	0.0000	1.000	1.00	0.816
	p8		PIF_6	0.994	0.0590	0.878	1.11	0.876	16.8	<.001
	p9		PIF_9	1.005	0.0585	0.890	1.12	0.872	17.2	<.001
2	p37	per_org	PIF_1	1.000	0.0000	1.000	1.00	0.676
	p2		PIF_4	1.335	0.1003	1.138	1.53	0.841	13.3	<.001
	p3		PIF_7	1.357	0.0995	1.162	1.55	0.911	13.6	<.001
	p40	need_sup	PIF_2	1.000	0.0000	1.000	1.00	0.828
	p5		PIF_5	1.076	0.0599	0.958	1.19	0.859	18.0	<.001
	p6		PIF_8	1.062	0.0525	0.960	1.17	0.897	20.3	<.001
	p43	dem_abil	PIF_3	1.000	0.0000	1.000	1.00	0.829
	p8		PIF_6	0.994	0.0590	0.878	1.11	0.825	16.8	<.001
	p9		PIF_9	1.005	0.0585	0.890	1.12	0.850	17.2	<.001

Variances and Covariances
						95% Confidence Intervals
Group	Label	Variable 1	Variable 2	Estimate	SE	Lower	Upper	β	z	p
1	p11	PIF_1	PIF_1	0.996	0.1648	0.6732	1.319	0.486	6.04	<.001
	p12	PIF_4	PIF_4	0.443	0.1149	0.2183	0.669	0.191	3.86	<.001
	p13	PIF_7	PIF_7	0.414	0.1146	0.1895	0.639	0.176	3.61	<.001
	p14	PIF_2	PIF_2	0.632	0.1146	0.4076	0.857	0.263	5.52	<.001
	p15	PIF_5	PIF_5	0.944	0.1627	0.6249	1.263	0.315	5.80	<.001
	p16	PIF_8	PIF_8	0.233	0.0728	0.0907	0.376	0.104	3.21	0.001
	p17	PIF_3	PIF_3	0.773	0.1388	0.5006	1.045	0.335	5.57	<.001
	p18	PIF_6	PIF_6	0.459	0.0960	0.2713	0.648	0.232	4.79	<.001
	p19	PIF_9	PIF_9	0.487	0.1002	0.2904	0.683	0.239	4.86	<.001
	p20	per_org	per_org	1.052	0.2168	0.6266	1.476	1.000	4.85	<.001
	p21	need_sup	need_sup	1.776	0.3143	1.1598	2.392	1.000	5.65	<.001
	p22	dem_abil	dem_abil	1.537	0.2853	0.9780	2.096	1.000	5.39	<.001
	p23	per_org	need_sup	0.991	0.2024	0.5947	1.388	0.725	4.90	<.001
	p24	per_org	dem_abil	0.857	0.1859	0.4928	1.222	0.674	4.61	<.001
	p25	need_sup	dem_abil	1.493	0.2615	0.9801	2.005	0.904	5.71	<.001
2	p47	PIF_1	PIF_1	0.923	0.1002	0.7269	1.120	0.543	9.21	<.001
	p48	PIF_4	PIF_4	0.573	0.0817	0.4131	0.733	0.293	7.02	<.001
	p49	PIF_7	PIF_7	0.293	0.0658	0.1636	0.422	0.170	4.44	<.001
	p50	PIF_2	PIF_2	0.629	0.0777	0.4764	0.781	0.314	8.09	<.001
	p51	PIF_5	PIF_5	0.565	0.0760	0.4163	0.714	0.263	7.44	<.001
	p52	PIF_8	PIF_8	0.376	0.0605	0.2576	0.495	0.195	6.22	<.001
	p53	PIF_3	PIF_3	0.642	0.0852	0.4749	0.809	0.313	7.53	<.001
	p54	PIF_6	PIF_6	0.651	0.0854	0.4835	0.818	0.319	7.62	<.001
	p55	PIF_9	PIF_9	0.546	0.0776	0.3944	0.698	0.278	7.04	<.001
	p56	per_org	per_org	0.778	0.1287	0.5256	1.030	1.000	6.05	<.001
	p57	need_sup	need_sup	1.372	0.1779	1.0234	1.721	1.000	7.71	<.001
	p58	dem_abil	dem_abil	1.407	0.1873	1.0401	1.775	1.000	7.51	<.001
	p59	per_org	need_sup	0.727	0.1081	0.5152	0.939	0.704	6.73	<.001
	p60	per_org	dem_abil	0.705	0.1084	0.4925	0.917	0.674	6.50	<.001
	p61	need_sup	dem_abil	1.115	0.1447	0.8317	1.399	0.803	7.71	<.001

Intercepts
					95% Confidence Intervals
Group	Label	Variable	Intercept	SE	Lower	Upper	z	p
1	p10	PIF_3	5.432	0.146	5.146	5.718	37.221	<.001
	p26	PIF_1	4.611	0.126	4.364	4.858	36.588	<.001
	p27	PIF_4	4.769	0.155	4.464	5.073	30.739	<.001
	p28	PIF_7	4.693	0.157	4.385	5.000	29.878	<.001
	p29	PIF_2	5.056	0.152	4.758	5.355	33.176	<.001
	p30	PIF_5	4.547	0.164	4.225	4.869	27.685	<.001
	p31	PIF_8	4.932	0.157	4.625	5.239	31.514	<.001
	p32	PIF_6	5.289	0.142	5.010	5.567	37.197	<.001
	p33	PIF_9	5.399	0.144	5.117	5.681	37.557	<.001
	p34	per_org	0.000	0.000	0.000	0.000
	p35	need_sup	0.000	0.000	0.000	0.000
	p36	dem_abil	0.000	0.000	0.000	0.000
2	p10	PIF_3	5.432	0.146	5.146	5.718	37.221	<.001
	p26	PIF_1	4.611	0.126	4.364	4.858	36.588	<.001
	p27	PIF_4	4.769	0.155	4.464	5.073	30.739	<.001
	p28	PIF_7	4.693	0.157	4.385	5.000	29.878	<.001
	p29	PIF_2	5.056	0.152	4.758	5.355	33.176	<.001
	p30	PIF_5	4.547	0.164	4.225	4.869	27.685	<.001
	p31	PIF_8	4.932	0.157	4.625	5.239	31.514	<.001
	p32	PIF_6	5.289	0.142	5.010	5.567	37.197	<.001
	p33	PIF_9	5.399	0.144	5.117	5.681	37.557	<.001
	p70	per_org	0.102	0.131	-0.156	0.360	0.775	0.438
	p71	need_sup	-0.230	0.170	-0.564	0.103	-1.355	0.175
	p72	dem_abil	-0.328	0.165	-0.651	-0.004	-1.984	0.047

References

[1] The jamovi project (2025). jamovi. (Version 2.7) [Computer Software]. Retrieved from https://www.jamovi.org.

[2] R Core Team (2025). R: A Language and environment for statistical computing. (Version 4.5) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2025-05-25).

[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.