Personal Information

Dereje Waktola Gudicha

Post-doctoral Researcher


  • BSc. in Statistics, Addis Ababa University, Addis Ababa, Ethiopia
  • MSc. in Statistics, Addis Ababa University, Addis Ababa, Ethiopia
  • MSc. in Social and Behavioral Science with specialization in Methodology and Statistics, Tilburg University, Tilburg, The Netherlands.
  • PhD. in Statistics, Tilburg University, Tilburg, The Netherlands


Research Interests

  • Mixture modeling for analyzing unobserved clusters of subjects by leveraging high-dimensional data
  • Power analysis for determining sample size and analyzing the feasibility of study design
  • Longitudinal analytic methods for identifying diseases markers and predicting clinical outcomes
  • Growth standards for fetal biometrics and biochemical markers



  1. Gudicha, D.W., Schmittman, V.D, and Vermunt, J.K. (2015). Power computation for likelihood ratio tests for the transition parameters in latent Markov models. Structural Equation Modeling: A multidisciplinary Journal, 1-12.
  2. Gudicha, D.W., Tekle, F.B, and Vermunt, J.K.(2016). Power and Sample Size Computation for Wald Tests in Latent Class Models. Journal of Classification, 33(1): 30-51.
  3. Gudicha, D.W., Schmittman, V.D, Tekle, F.B, and Vermunt, J.K. (2016). Power Analysis for the Likelihood-Ratio Test in Latent Markov Models: Short-cutting the bootstrap p-value based method. Multivariate Behavioral Research, 51(5): 649-660.
  4. Gudicha, D.W., Schmittman, V.D, and Vermunt, J.K. (2017). Statistical Power of Likelihood-Ratio and Wald Tests in Latent Class Models with Covariates. Behavior Research Methods, 49(5): 1824-1837.
  5. Tekle, F.B, Gudicha, D.W., and Vermunt, J.K. (2016). Power analysis for Bootstrap Likelihood Ratio Test for the number of classes in Latent Class Models. Advances in Data Analysis and Classification, 10(2), 209-224.
  6. Tarca, A.L., Romero R, Gudicha, D.W., Erez, O., Hernandez-Andrade, E., Yeo, L., Bhatti,G., Parcora, P., Maymon, and E., Hassan,S.(2018). New customized fetal growth standard for African American women: the PRB/NICHD Detroit study. American Journal of Obstetrics and Genecology, 218(2), S679-S691.e4.
  7. Kabiri, D., Romero, R., Gudicha, D.W., Hernandez-Andrade,E., Pacora,P. , Tirosh,N., Tirosh,D., Yeo,L., Erez, O., Hassan,S., and Tarca,A.L (2019). Prediction of adverse perinatal outcomes by fetal biometry: A comparison of customized and population-based standards.  Ultrasound in Obstetrics and Gynecology, DOI:10.1002/uog.20299.
  8. Gomez-Lopez, N., Romero, R., Panaitescu, B., Miller, D., Zhou, C., Gudicha, D.W., Tarca, A.L., Para, R., Hassan, S., and Hsu, C. (2019). Gasdermin D: In Vivo Evidence of Pyroptosis in Spontaneous Labor at Term.  Journal of Maternal-Fetal and Neonatal Medicine, DOI: 10.1080/14767058.2019.1610740.
  9. Tarca AL, Romero R, Benshalom-Tirosh N, Than NG, Gudicha,  W, Done B, Pacora, P., Chaiworapongsa, T., Panaitescu, B., Tirosh, D., Gomeze-Lopez, N., Draghici., S., Erez, O.. (2019).  The prediction of early preeclampsia: Results from a longitudinal proteomics study. PLoS ONE 14(6): e0217273. pone.0217273.