library(lavaan)
## Warning: package 'lavaan' was built under R version 4.2.3
## This is lavaan 0.6-15
## lavaan is FREE software! Please report any bugs.
library(lavaanPlot) # for plotting later
## Warning: package 'lavaanPlot' was built under R version 4.2.2
#do not forget to set working directory!
# Model (1) Team Sport; t_Performance= (Self_Confidence(Cognitive , Somatic))
# Model (2) Indv Sport; i_Performance= (Self_Confidence(Cognitive , Somatic))
############
# Model(1) , n=142
Mi <- as.matrix(read.csv("matrix i.csv", row.names = 1))
Mi
## Self_Confidence_i Performance_i Cognitive_i Somatic_i
## Self_Confidence_i 1.00 0.66 -0.38 -0.46
## Performance_i 0.66 1.00 -0.55 -0.48
## Cognitive_i -0.38 -0.55 1.00 NA
## Somatic_i -0.46 -0.48 0.47 1.00
# Model(1) :
###### Indirect effect ,we use labeled syntax
Performance_i_pa<-'
Self_Confidence_i ~ a_co * Cognitive_i + a_so * Somatic_i
Performance_i ~ b * Self_Confidence_i+ Cognitive_i + Somatic_i
ind_co := a_co * b
ind_so := a_so * b'
Performance_i_pa <- sem(model= Performance_i_pa, sample.cov = Mi,sample.nobs = 142)
Performance_i_pa
## lavaan 0.6.15 ended normally after 1 iteration
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
##
## Number of observations 142
##
## Model Test User Model:
##
## Test statistic 0.000
## Degrees of freedom 0
summary(Performance_i_pa, header = FALSE, standardize = TRUE, ci = TRUE)
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## Self_Confidence_i ~
## Cogntv_ (a_co) -0.210 0.083 -2.547 0.011 -0.372 -0.048
## Somatc_ (a_so) -0.361 0.083 -4.375 0.000 -0.523 -0.199
## Performance_i ~
## Slf_Cn_ (b) 0.492 0.065 7.573 0.000 0.365 0.619
## Cogntv_ -0.313 0.065 -4.788 0.000 -0.441 -0.185
## Somatc_ -0.107 0.068 -1.565 0.118 -0.240 0.027
## Std.lv Std.all
##
## -0.210 -0.210
## -0.361 -0.361
##
## 0.492 0.492
## -0.313 -0.313
## -0.107 -0.107
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .Self_Confidnc_ 0.749 0.089 8.426 0.000 0.575 0.923
## .Performance_i 0.449 0.053 8.426 0.000 0.344 0.553
## Std.lv Std.all
## 0.749 0.754
## 0.449 0.452
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## ind_co -0.103 0.043 -2.414 0.016 -0.187 -0.019
## ind_so -0.178 0.047 -3.788 0.000 -0.270 -0.086
## Std.lv Std.all
## -0.103 -0.103
## -0.178 -0.178
lavaanPlot(model = Performance_i_pa, coefs = TRUE, covs = TRUE, stars = "regress")
#############################################################
#######
# Model(2) , n= 128
Mt <- as.matrix(read.csv("matrix t.csv", row.names = 1))
Mt
## Self_Confidence_t Performance_t Cognitive_t Somatic_t
## Self_Confidence_t 1.00 0.13 -0.53 -0.27
## Performance_t 0.13 1.00 0.14 0.02
## Cognitive_t -0.53 0.14 1.00 0.56
## Somatic_t -0.27 0.02 0.56 1.00
# Model(2)
###### Indirect effect ,we use labeled syntax
Performance_t_pa<-'
Self_Confidence_t ~ a_cot * Cognitive_t + a_sot * Somatic_t
Performance_t ~ bt * Self_Confidence_t+ Cognitive_t + Somatic_t
ind_cot := a_cot * bt
ind_sot := a_sot * bt'
Performance_t_pa <- sem(model= Performance_t_pa, sample.cov = Mt,sample.nobs = 128)
Performance_t_pa
## lavaan 0.6.15 ended normally after 1 iteration
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
##
## Number of observations 128
##
## Model Test User Model:
##
## Test statistic 0.000
## Degrees of freedom 0
summary(Performance_t_pa, header = FALSE, standardize = TRUE, ci = TRUE)
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## Self_Confidence_t ~
## Cgntv_t (a_ct) -0.552 0.090 -6.104 0.000 -0.729 -0.375
## Somtc_t (a_st) 0.039 0.090 0.432 0.666 -0.138 0.216
## Performance_t ~
## Slf_Cn_ (bt) 0.288 0.100 2.880 0.004 0.092 0.483
## Cgntv_t 0.346 0.116 2.985 0.003 0.119 0.574
## Somtc_t -0.096 0.102 -0.943 0.346 -0.297 0.104
## Std.lv Std.all
##
## -0.552 -0.552
## 0.039 0.039
##
## 0.288 0.288
## 0.346 0.346
## -0.096 -0.096
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .Self_Confdnc_t 0.712 0.089 8.000 0.000 0.538 0.887
## .Performance_t 0.909 0.114 8.000 0.000 0.686 1.132
## Std.lv Std.all
## 0.712 0.718
## 0.909 0.916
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## ind_cot -0.159 0.061 -2.605 0.009 -0.278 -0.039
## ind_sot 0.011 0.026 0.427 0.669 -0.040 0.063
## Std.lv Std.all
## -0.159 -0.159
## 0.011 0.011
lavaanPlot(model = Performance_t_pa, coefs = TRUE, covs = TRUE, stars = "regress")