# imposeStart: Specify starting values from a lavaan output In semTools: Useful Tools for Structural Equation Modeling

## Description

This function will save the parameter estimates of a lavaan output and impose those parameter estimates as starting values for another analysis model. The free parameters with the same names or the same labels across two models will be imposed the new starting values. This function may help to increase the chance of convergence in a complex model (e.g., multitrait-multimethod model or complex longitudinal invariance model).

## Usage

 `1` ```imposeStart(out, expr, silent = TRUE) ```

## Arguments

 `out` The `lavaan` output that users wish to use the parameter estimates as staring values for an analysis model `expr` The original code that users use to run a lavaan model `silent` Logical to print the parameter table with new starting values

## Value

A fitted lavaan model

## Author(s)

Sunthud Pornprasertmanit (psunthud@gmail.com)

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115``` ```## The following example show that the longitudinal weak invariance model ## using effect coding was not convergent with three time points but convergent ## with two time points. Thus, the parameter estimates from the model with ## two time points are used as starting values of the three time points. ## The model with new starting values is convergent properly. weak2time <- ' # Loadings f1t1 =~ LOAD1*y1t1 + LOAD2*y2t1 + LOAD3*y3t1 f1t2 =~ LOAD1*y1t2 + LOAD2*y2t2 + LOAD3*y3t2 # Factor Variances f1t1 ~~ f1t1 f1t2 ~~ f1t2 # Factor Covariances f1t1 ~~ f1t2 # Error Variances y1t1 ~~ y1t1 y2t1 ~~ y2t1 y3t1 ~~ y3t1 y1t2 ~~ y1t2 y2t2 ~~ y2t2 y3t2 ~~ y3t2 # Error Covariances y1t1 ~~ y1t2 y2t1 ~~ y2t2 y3t1 ~~ y3t2 # Factor Means f1t1 ~ NA*1 f1t2 ~ NA*1 # Measurement Intercepts y1t1 ~ INT1*1 y2t1 ~ INT2*1 y3t1 ~ INT3*1 y1t2 ~ INT4*1 y2t2 ~ INT5*1 y3t2 ~ INT6*1 # Constraints for Effect-coding Identification LOAD1 == 3 - LOAD2 - LOAD3 INT1 == 0 - INT2 - INT3 INT4 == 0 - INT5 - INT6 ' model2time <- lavaan(weak2time, data = exLong) weak3time <- ' # Loadings f1t1 =~ LOAD1*y1t1 + LOAD2*y2t1 + LOAD3*y3t1 f1t2 =~ LOAD1*y1t2 + LOAD2*y2t2 + LOAD3*y3t2 f1t3 =~ LOAD1*y1t3 + LOAD2*y2t3 + LOAD3*y3t3 # Factor Variances f1t1 ~~ f1t1 f1t2 ~~ f1t2 f1t3 ~~ f1t3 # Factor Covariances f1t1 ~~ f1t2 + f1t3 f1t2 ~~ f1t3 # Error Variances y1t1 ~~ y1t1 y2t1 ~~ y2t1 y3t1 ~~ y3t1 y1t2 ~~ y1t2 y2t2 ~~ y2t2 y3t2 ~~ y3t2 y1t3 ~~ y1t3 y2t3 ~~ y2t3 y3t3 ~~ y3t3 # Error Covariances y1t1 ~~ y1t2 y2t1 ~~ y2t2 y3t1 ~~ y3t2 y1t1 ~~ y1t3 y2t1 ~~ y2t3 y3t1 ~~ y3t3 y1t2 ~~ y1t3 y2t2 ~~ y2t3 y3t2 ~~ y3t3 # Factor Means f1t1 ~ NA*1 f1t2 ~ NA*1 f1t3 ~ NA*1 # Measurement Intercepts y1t1 ~ INT1*1 y2t1 ~ INT2*1 y3t1 ~ INT3*1 y1t2 ~ INT4*1 y2t2 ~ INT5*1 y3t2 ~ INT6*1 y1t3 ~ INT7*1 y2t3 ~ INT8*1 y3t3 ~ INT9*1 # Constraints for Effect-coding Identification LOAD1 == 3 - LOAD2 - LOAD3 INT1 == 0 - INT2 - INT3 INT4 == 0 - INT5 - INT6 INT7 == 0 - INT8 - INT9 ' ### The following command does not provide convergent result # model3time <- lavaan(weak3time, data = exLong) ### Use starting values from the model with two time points model3time <- imposeStart(model2time, lavaan(weak3time, data = exLong)) summary(model3time) ```

semTools documentation built on Jan. 13, 2021, 8:09 p.m.