Enhancement: `tab_fa` for presenting {psych} output with factor names

[Claudiu Papasteri]

I love using sjPlot for presenting nice tables, but I like to do the analyses using the original functions that are wrapped by sjPlot. For example sjPlot::tab_fa() nicely wraps psych::fa() but does not return the fa class object with all relevant info. Fortunately, sjPlot::tab_fa() accepts these object and just outputs them in nice tables with one simple shortcoming: it renames the factors. This behaviour is hardcoded at line 332. We have argument var.labels for item names. Simple fixes would be either to have an argument fac.labels or just store factor names for fa class objects and print those.

library(psych)
library(sjPlot)

efa_bfi <- psych::fa(na.omit(psych::bfi[, 1:25]), nfactors = 6, rotate = "oblimin")
#> Loading required namespace: GPArotation
efa_bfi$loadings
#> 
#> Loadings:
#>    MR2    MR1    MR3    MR5    MR4    MR6   
#> A1        -0.106        -0.563         0.288
#> A2                       0.701              
#> A3        -0.103         0.628         0.120
#> A4                0.191  0.410 -0.126  0.130
#> A5 -0.166 -0.187         0.460  0.108  0.218
#> C1                0.548         0.191       
#> C2         0.142  0.674                0.184
#> C3                0.562                     
#> C4               -0.675                0.291
#> C5  0.153  0.176 -0.553         0.101       
#> E1 -0.136  0.600  0.101 -0.130              
#> E2         0.682                            
#> E3        -0.332         0.153  0.386  0.240
#> E4        -0.532         0.219         0.278
#> E5  0.150 -0.393  0.263         0.242       
#> N1  0.848                                   
#> N2  0.833                                   
#> N3  0.674  0.135                            
#> N4  0.430  0.433 -0.137                     
#> N5  0.437  0.238         0.174 -0.128  0.149
#> O1                              0.566       
#> O2  0.116                      -0.420  0.305
#> O3                              0.655       
#> O4         0.355         0.152  0.364       
#> O5                             -0.491  0.351
#> 
#>                  MR2   MR1   MR3   MR5   MR4   MR6
#> SS loadings    2.391 1.919 1.992 1.775 1.640 0.704
#> Proportion Var 0.096 0.077 0.080 0.071 0.066 0.028
#> Cumulative Var 0.096 0.172 0.252 0.323 0.389 0.417
sjPlot::tab_fa(efa_bfi)
#> Cronbach's Alpha can only be calculated when having a data frame with each component / variable as column.

Factor Analysis

	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5	Factor 6
A1	0.09	-0.11	0.07	-0.56	0.03	0.29
A2	0.05	-0.04	0.07	0.70	-0.00	-0.07
A3	-0.03	-0.10	0.03	0.63	0.06	0.12
A4	-0.07	-0.08	0.19	0.41	-0.13	0.13
A5	-0.17	-0.19	0.01	0.46	0.11	0.22
C1	0.02	0.07	0.55	-0.04	0.19	0.09
C2	0.07	0.14	0.67	0.02	0.10	0.18
C3	0.01	0.06	0.56	0.07	-0.05	0.06
C4	0.05	0.08	-0.67	-0.05	0.04	0.29
C5	0.15	0.18	-0.55	-0.00	0.10	0.04
E1	-0.14	0.60	0.10	-0.13	-0.08	0.09
E2	0.05	0.68	-0.03	-0.08	-0.07	0.02
E3	0.01	-0.33	0.00	0.15	0.39	0.24
E4	-0.05	-0.53	0.03	0.22	0.01	0.28
E5	0.15	-0.39	0.26	0.05	0.24	0.05
N1	0.85	-0.10	0.00	-0.07	-0.05	0.00
N2	0.83	-0.05	0.02	-0.04	0.00	-0.08
N3	0.67	0.14	-0.03	0.08	0.03	0.08
N4	0.43	0.43	-0.14	0.08	0.09	0.06
N5	0.44	0.24	-0.00	0.17	-0.13	0.15
O1	-0.05	-0.03	0.07	-0.04	0.57	0.07
O2	0.12	-0.02	-0.08	0.09	-0.42	0.31
O3	-0.01	-0.10	0.01	0.04	0.66	0.04
O4	0.08	0.35	-0.03	0.15	0.36	-0.01
O5	0.04	-0.05	-0.03	-0.03	-0.49	0.35

^{Created on 2023-05-18 with reprex v2.0.2}