Nina Loginova

Statistical Consultant | Biostatistician

I'm a Biostatistician with a strong background in theoretical mathematics and extensive experience in clinical trials.

Expertise in multiple testing, non-parametric statistics, and adaptive trial design

Complex statistical concepts made easy to understand

Proficiency in SAS and R

Experienced university lecturer

Education

  • Nonparametric test theory, 2014-2015

    Humboldt University Berlin, Berlin, Germany

  • B.Sc. Mathematics, 2009-2012

    Free University of Berlin, Berlin, Germany

Expertise

  • Descriptive Statistics
  • Probability Theorie
  • Statistical Testing
  • Non-Parametric Methods
  • Adaptive Study Design
  • Bayesian Statistics
  • Predictive Big Data Modeling

Software, Statistical Methodology, Services

Software

SAS

R

Python

Matlab

PASS

nQuery

Statistical Methodology

Multiple Testing

Adaptive Study Design

Kaplan-Meier Survival Analysis

Regression Analysis

ANOVA / ANCOVA

Assay Statistics

Bland-Altman Analysis

Clinical Services

Statistical consulting

Sample size estimation

Randomization

Statistical analysis plan (SAP)

Programming of TLGs

CDISC SDTM & ADaM

Therapeutic Areas

Neurology

Immunology

Immune Cell Diagnostics

Medical Devices

Dermatology

Gastroenterology

Hepatology

Experience

INDUSTRY EXPERIENCE

 
 
 
 
 

Statistician

FGK Clinical Research GmbH

2021 - 2023 Berlin, Germany
Sample size estimation and power calculation, randomization
Statistical sections of study protocols
Statistical analysis plan (SAP)
Statistical consulting of sponsors and project managers
Generation of biometric reports, programming of TLGs
 
 
 
 
 

Biostatistics Consulter

2019 - 2020 Berlin, Germany
Evaluation and validation of assays
Planning statistical analysis
Sample size estimation
Evaluation of the results
 
 
 
 
 

Clinical Data Programmer II

PAREXEL International GmbH

2016 - 2017 Berlin, Germany
Data management with SAS
Development of SAS macros
Mapping to CDISC data standards according to ICH-GCP
Data validation, external data reconciliation, quality control
 
 
 
 
 

Research Assistant. Research group "Stochastic Algorithms and Nonparametric Statistics"

Weierstrass Institute for Applied Analysis and Stochastics

2014-2015 Berlin, Germany
Design of experiments
Multiple Testing with focus on FDR control
Statistical modelling and analysis of neuroeconomic and epigenetic data
Regression analysis, ANOVA

Experience

TEACHING EXPERIENCE

 
 
 
 
 

Statistics

HTW Berlin - University of Applied Sciences / HWR Berlin

2024 – Present Berlin, Germany
 
 
 
 
 

Advanced Mathematics I & II

HTW Berlin - University of Applied Sciences

2019 – 2021 Berlin, Germany
 
 
 
 
 

Statistics for Psychologists I & II, Statistics and Business Mathematics

FHM Berlin – University of Applied Sciences

2018 – 2021 Berlin, Germany

Education & Training

SELECTION

Adaptive Designs and Multiple Testing Procedures

Adaptive Designs and Multiple Testing Procedures

SAS® Macro Language 1: Essentials

Tipping Point Analyses – Introduction & Case

RPACT: Introduction and new features

Design of Experiments under Uncertainty

Publications

Survival analysis is a key statistical method in clinical research, used to analyze the time until an event of interest, such as death, …

kaplan-meier

Computing and approximating multivariate chi-square probabilities. The multivariate chi-squared distribution is an extension of the …

chi square

Adaptive designs are becoming increasingly important in clinical trials, reflecting a shift towards more flexible and efficient study methodologies. …

adaptive design

In clinical trials, one of the fundamental goals is to understand the effect of a treatment or intervention. To achieve this, we need to clearly define what exactly we are trying to measure. This is where the concept of estimands becomes crucial …

estimands

A framework in the literature for the applicability of the different methods to handle missingness is based on a classification according to the following missingness mechanisms …

missing data