Nice html table for lavaan structure equation model fitted objects

nice_sem(
  x,
  standardized = TRUE,
  show_fitmeasures = c(CFI = "cfi", TLI = "tli", RMSEA = "rmsea", `RMSEA ci lower` =
    "rmsea.ci.lower", SRMR = "srmr", AIC = "aic", BIC = "bic"),
  remove_cols = NULL,
  show_ci = TRUE,
  round = 2,
  ...
)

Arguments

x: An object returned from the lavaan sem or cfa function.
standardized: If TRUE, standardized estimates are shown.
show_fitmeasures: A named vector with fit measures.
remove_cols: Either column number or column names to be removed.
show_ci: If TRUE, adds columns with 95% confidence intervals.
round: Number of digits to round numeric values.
...: Further arguments passed to the nice_table() function.

Examples

nice_sem(wmisc:::lavaan_fit)


  Table
Structure equation model
    
parameter
      Beta
      
        95% CI
      
      se
      z
      p
    
lower
      upper
    
Latent variables
    
remediation → RU_02
0.90
0.88
0.92
0.01
91.87
<.001
remediation → RM_01
0.90
0.88
0.92
0.01
91.94
<.001
remediation → RU_03
0.87
0.85
0.90
0.01
73.12
<.001
remediation → RM_02
0.89
0.87
0.91
0.01
83.82
<.001
development → RE_01
0.91
0.88
0.94
0.02
59.10
<.001
development → RE_02
0.91
0.88
0.94
0.02
59.26
<.001
goal → RZ_02
0.88
0.85
0.90
0.01
63.27
<.001
goal → RZ_01
0.91
0.88
0.93
0.01
72.00
<.001
Covariances
    
remediation ↔ development
0.59
0.52
0.65
0.03
18.43
<.001
remediation ↔ goal
0.80
0.76
0.84
0.02
40.24
<.001
development ↔ goal
0.74
0.70
0.79
0.02
30.32
<.001
Variances
    
RU_02
0.19
0.15
0.22
0.02
10.58
<.001
RM_01
0.19
0.15
0.22
0.02
10.57
<.001
RU_03
0.24
0.20
0.28
0.02
11.55
<.001
RM_02
0.21
0.17
0.24
0.02
10.94
<.001
RE_01
0.18
0.12
0.23
0.03
6.39
<.001
RE_02
0.18
0.12
0.23
0.03
6.33
<.001
RZ_02
0.23
0.19
0.28
0.02
9.59
<.001
RZ_01
0.18
0.13
0.22
0.02
7.84
<.001
remediation
1.00
1.00
1.00
0.00



development
1.00
1.00
1.00
0.00



goal
1.00
1.00
1.00
0.00



Intercepts
    
RU_02
2.94
2.75
3.13
0.10
30.00
<.001
RM_01
2.72
2.54
2.90
0.09
29.54
<.001
RU_03
2.69
2.51
2.87
0.09
29.45
<.001
RM_02
2.48
2.32
2.65
0.09
28.93
<.001
RE_01
3.01
2.82
3.21
0.10
30.13
<.001
RE_02
2.83
2.64
3.01
0.09
29.77
<.001
RZ_02
2.72
2.54
2.90
0.09
29.54
<.001
RZ_01
3.00
2.81
3.20
0.10
30.11
<.001
remediation
0.00
0.00
0.00
0.00



development
0.00
0.00
0.00
0.00



goal
0.00
0.00
0.00
0.00



Modelfit
    
N parameters
27.00









Observations
554.00









Χ²(17) / p-value
142.89
0.00







CFI
0.97









TLI
0.95









RMSEA
0.12









RMSEA ci lower
0.10









SRMR
0.03









AIC
9644.88









BIC
9761.44









 Note. The estimation method employed in this analysis is Maximum Likelihood (ML). The Non-Linear Minimization, Bounded (nlminb) algorithm was applied for optimization. Missing data were addressed using the Full Information Maximum Likelihood (FIML) approach. The analysis was performed with the lavaan package in R (Yves Rosseel, Terrence D. Jorgensen, Luc De Wilde, 2025).
    
nice_sem(wmisc:::lavaan_fit, standardized = FALSE, show_ci = FALSE)


  Table
Structure equation model
    
parameter
      b
      se
      z
      p
    
Latent variables
    
remediation → RU_02
1.00
0.04
27.13
<.001
remediation → RM_01
1.01
0.04
27.13
<.001
remediation → RU_03
0.94
0.04
25.62
<.001
remediation → RM_02
1.07
0.04
26.55
<.001
development → RE_01
0.99
0.04
25.74
<.001
development → RE_02
0.99
0.04
25.78
<.001
goal → RZ_02
0.99
0.04
25.22
<.001
goal → RZ_01
0.95
0.04
26.55
<.001
Covariances
    
remediation ↔ development
0.59
0.03
18.43
<.001
remediation ↔ goal
0.80
0.02
40.24
<.001
development ↔ goal
0.74
0.02
30.32
<.001
Variances
    
RU_02
0.23
0.02
12.25
<.001
RM_01
0.23
0.02
12.23
<.001
RU_03
0.28
0.02
13.34
<.001
RM_02
0.30
0.02
12.66
<.001
RE_01
0.21
0.03
6.71
<.001
RE_02
0.21
0.03
6.65
<.001
RZ_02
0.30
0.03
10.57
<.001
RZ_01
0.20
0.02
8.47
<.001
remediation
1.00
0.00



development
1.00
0.00



goal
1.00
0.00



Intercepts
    
RU_02
3.27
0.05
69.18
<.001
RM_01
3.03
0.05
64.07
<.001
RU_03
2.89
0.05
63.23
<.001
RM_02
2.98
0.05
58.49
<.001
RE_01
3.30
0.05
70.93
<.001
RE_02
3.07
0.05
66.50
<.001
RZ_02
3.08
0.05
64.09
<.001
RZ_01
3.16
0.04
70.62
<.001
remediation
0.00
0.00



development
0.00
0.00



goal
0.00
0.00



Modelfit
    
N parameters
27.00





Observations
554.00





Χ²(17) / p-value
142.89
0.00



CFI
0.97





TLI
0.95





RMSEA
0.12





RMSEA ci lower
0.10





SRMR
0.03





AIC
9644.88





BIC
9761.44





 Note. The estimation method employed in this analysis is Maximum Likelihood (ML). The Non-Linear Minimization, Bounded (nlminb) algorithm was applied for optimization. Missing data were addressed using the Full Information Maximum Likelihood (FIML) approach. The analysis was performed with the lavaan package in R (Yves Rosseel, Terrence D. Jorgensen, Luc De Wilde, 2025).
    
nice_sem(
 wmisc:::lavaan_fit,
 show_fitmeasures = c(
  FI = "cfi", TLI = "tli", RMSEA = "rmsea",
  "SRMR" = "srmr"
 ),
 remove_cols = c("se", "z")
)


  Table
Structure equation model
    
parameter
      Beta
      
        95% CI
      
      p
    
lower
      upper
    
Latent variables
    
remediation → RU_02
0.90
0.88
0.92
<.001
remediation → RM_01
0.90
0.88
0.92
<.001
remediation → RU_03
0.87
0.85
0.90
<.001
remediation → RM_02
0.89
0.87
0.91
<.001
development → RE_01
0.91
0.88
0.94
<.001
development → RE_02
0.91
0.88
0.94
<.001
goal → RZ_02
0.88
0.85
0.90
<.001
goal → RZ_01
0.91
0.88
0.93
<.001
Covariances
    
remediation ↔ development
0.59
0.52
0.65
<.001
remediation ↔ goal
0.80
0.76
0.84
<.001
development ↔ goal
0.74
0.70
0.79
<.001
Variances
    
RU_02
0.19
0.15
0.22
<.001
RM_01
0.19
0.15
0.22
<.001
RU_03
0.24
0.20
0.28
<.001
RM_02
0.21
0.17
0.24
<.001
RE_01
0.18
0.12
0.23
<.001
RE_02
0.18
0.12
0.23
<.001
RZ_02
0.23
0.19
0.28
<.001
RZ_01
0.18
0.13
0.22
<.001
remediation
1.00
1.00
1.00

development
1.00
1.00
1.00

goal
1.00
1.00
1.00

Intercepts
    
RU_02
2.94
2.75
3.13
<.001
RM_01
2.72
2.54
2.90
<.001
RU_03
2.69
2.51
2.87
<.001
RM_02
2.48
2.32
2.65
<.001
RE_01
3.01
2.82
3.21
<.001
RE_02
2.83
2.64
3.01
<.001
RZ_02
2.72
2.54
2.90
<.001
RZ_01
3.00
2.81
3.20
<.001
remediation
0.00
0.00
0.00

development
0.00
0.00
0.00

goal
0.00
0.00
0.00

Modelfit
    
N parameters
27.00





Observations
554.00





Χ²(17) / p-value
142.89
0.00



FI
0.97





TLI
0.95





RMSEA
0.12





SRMR
0.03





 Note. The estimation method employed in this analysis is Maximum Likelihood (ML). The Non-Linear Minimization, Bounded (nlminb) algorithm was applied for optimization. Missing data were addressed using the Full Information Maximum Likelihood (FIML) approach. The analysis was performed with the lavaan package in R (Yves Rosseel, Terrence D. Jorgensen, Luc De Wilde, 2025).

parameter	Beta	95% CI		se	z	p
Table Structure equation model
parameter	Beta	lower	upper	se	z	p
Latent variables
remediation → RU_02	0.90	0.88	0.92	0.01	91.87	<.001
remediation → RM_01	0.90	0.88	0.92	0.01	91.94	<.001
remediation → RU_03	0.87	0.85	0.90	0.01	73.12	<.001
remediation → RM_02	0.89	0.87	0.91	0.01	83.82	<.001
development → RE_01	0.91	0.88	0.94	0.02	59.10	<.001
development → RE_02	0.91	0.88	0.94	0.02	59.26	<.001
goal → RZ_02	0.88	0.85	0.90	0.01	63.27	<.001
goal → RZ_01	0.91	0.88	0.93	0.01	72.00	<.001
Covariances
remediation ↔ development	0.59	0.52	0.65	0.03	18.43	<.001
remediation ↔ goal	0.80	0.76	0.84	0.02	40.24	<.001
development ↔ goal	0.74	0.70	0.79	0.02	30.32	<.001
Variances
RU_02	0.19	0.15	0.22	0.02	10.58	<.001
RM_01	0.19	0.15	0.22	0.02	10.57	<.001
RU_03	0.24	0.20	0.28	0.02	11.55	<.001
RM_02	0.21	0.17	0.24	0.02	10.94	<.001
RE_01	0.18	0.12	0.23	0.03	6.39	<.001
RE_02	0.18	0.12	0.23	0.03	6.33	<.001
RZ_02	0.23	0.19	0.28	0.02	9.59	<.001
RZ_01	0.18	0.13	0.22	0.02	7.84	<.001
remediation	1.00	1.00	1.00	0.00
development	1.00	1.00	1.00	0.00
goal	1.00	1.00	1.00	0.00
Intercepts
RU_02	2.94	2.75	3.13	0.10	30.00	<.001
RM_01	2.72	2.54	2.90	0.09	29.54	<.001
RU_03	2.69	2.51	2.87	0.09	29.45	<.001
RM_02	2.48	2.32	2.65	0.09	28.93	<.001
RE_01	3.01	2.82	3.21	0.10	30.13	<.001
RE_02	2.83	2.64	3.01	0.09	29.77	<.001
RZ_02	2.72	2.54	2.90	0.09	29.54	<.001
RZ_01	3.00	2.81	3.20	0.10	30.11	<.001
remediation	0.00	0.00	0.00	0.00
development	0.00	0.00	0.00	0.00
goal	0.00	0.00	0.00	0.00
Modelfit
N parameters	27.00
Observations	554.00
Χ²(17) / p-value	142.89	0.00
CFI	0.97
TLI	0.95
RMSEA	0.12
RMSEA ci lower	0.10
SRMR	0.03
AIC	9644.88
BIC	9761.44
Note. The estimation method employed in this analysis is Maximum Likelihood (ML). The Non-Linear Minimization, Bounded (nlminb) algorithm was applied for optimization. Missing data were addressed using the Full Information Maximum Likelihood (FIML) approach. The analysis was performed with the lavaan package in R (Yves Rosseel, Terrence D. Jorgensen, Luc De Wilde, 2025).