Data were analyzed using growth mixture modeling (GMM) and multinomial logistic regression.
The R(f) data were analyzed using various growth models.
Data was analyzed using latent growth curve modelling.
The current data were analyzed using latent growth modelling (LGM) approach.
Subscales of the IIEF were analyzed using longitudinal growth curves (Table 2).
The results were analyzed using Latent Growth Curve Modeling across the 24-months follow-up period.
Data collected at baseline, month 1, 2, 6 and 12 were analyzed using individual growth curve (IGC) models with the SAS Mixed Procedure.
Data were analyzed using latent class growth analysis (LCGA) and logistic regression.
Changes in plant growth over time were analyzed using the methods of classical growth analysis [ 52] and based on biomass and leaf area changes between the two consecutive harvests.
Student BMI data was analyzed using the CDC BMI growth charts, and reported in the four categories of underweight, normal weight, overweight, and obese.
