Miscellaneous functions for (1) data handling (e.g., grand-mean and group-mean centering, coding variables and reverse coding items, scale and cluster scores, reading and writing Excel and SPSS files), (2) descriptive statistics (e.g., frequency table, cross tabulation, effect size measures), (3) missing data (e.g., descriptive statistics for missing data, missing data pattern, Little's test of Missing Completely at Random, and auxiliary variable analysis), (4) multilevel data (e.g., multilevel descriptive statistics, within-group and between-group correlation matrix, multilevel confirmatory factor analysis, level-specific fit indices, cross-level measurement equivalence evaluation, multilevel composite reliability, and multilevel R-squared measures), (5) item analysis (e.g., confirmatory factor analysis, coefficient alpha and omega, between-group and longitudinal measurement equivalence evaluation), (6) statistical analysis (e.g., bootstrap confidence intervals, collinearity and residual diagnostics, dominance analysis, between- and within-subject analysis of variance, latent class analysis, t-test, z-test, sample size determination), and (7) functions to interact with 'Blimp' and 'Mplus'.

Easily import the MI-SUVI data sets. The user can import data sets with full metrics, percentiles, Z-scores, or rankings.
    Data is available at both the County and Zip Code Tabulation Area (ZCTA) levels. This package also includes a function to import 
    shape files for easy mapping and a function to access the full technical documentation. All data is sourced from the Michigan Department of Health and Human Services.

Provides methods to estimate serial intervals and time-varying case
  reproduction numbers from infectious disease outbreak data. Serial intervals measure
  the time between symptom onset in linked transmission pairs, while case reproduction 
  numbers quantify how many secondary cases each infected individual generates 
  over time. These parameters are essential for understanding transmission 
  dynamics, evaluating control measures, and informing public health responses. 
  The package implements the maximum likelihood framework from Vink et al. (2014) 
  <doi:10.1093/aje/kwu209> for serial interval estimation and the retrospective 
  method from Wallinga & Lipsitch (2007) <doi:10.1098/rspb.2006.3754> for 
  reproduction number estimation. Originally developed for scabies transmission 
  analysis but applicable to other infectious diseases including influenza, 
  COVID-19, and emerging pathogens. Designed for epidemiologists, public health 
  researchers, and infectious disease modelers working with outbreak surveillance 
  data.