Thesis and Dissertation Advisors - Statistics

---

[an error occurred while processing this directive]

---

[an error occurred while processing this directive]

---

DR. VICTORIA BRIONES
Education and Psychology Statistics - Data Analysis

DR. VICTORIA BRIONES graduated with a Ph.D. in Organizational Psychology from Columbia University. While completing her graduate studies, she taught applied regression analysis to graduate students in education and psychology. Students enjoyed her regression course because she was able to translate complex statistical concepts into a language that the “stats phobic� students could easily understand. Victoria was also an assistant lecturer in research methods (and received the highest mean evaluation for teaching performance). After graduating, she was a research vellow at Harvard University's Kennedy School of Government. As a fellow, she conducted statistical analyses and wrote articles on negotiation behavior and conflict resolution with her former dissertation adviser.

In the last two years, Victoria has worked as a statistical consultant, helping graduate students in psychology, education, nursing, biology, and business hone their study hypotheses, arrive at better operational definitions of their study variables, and improve procedures to increase the internal and/or external validity of their study. She also performed general statistical procedures such as reliability analyses, non-parametric tests (e.g., Mann-Whitney, Kruskal-Wallis, and chi-square tests), t-tests, analysis of variance (ANOVA), analysis of covariance (ANCOVA), exploratory factor analysis (EFA), and linear regression. Further, she conducted multivariate tests such as multivariate analysis of variance (MANOVA), logistic regression, and structural equation modeling (SEM; using AMOS, LISREL, and EQS). Victoria also created summary tables and graphs of statistical findings and helped students interpret their study results. More importantly, she enjoyed explaining basic statistical procedures and findings to clients who had a limited understanding of such concepts.

Scope: research methods, reliability analyses, t-tests, ANOVA, repeated-measures ANOVA, ANCOVA, exploratory and confirmatory factor analyses, multiple linear regression, logistic regression, MANOVA, structural equation modeling (AMOS, LISREL, and EQS)

Additional Information >>

---

JOHN BUCCI
Statistics - Mathematics - Economics - Finance - Business

John Bucci focused his Master’s studies in quantitative finance, specifically option pricing theory and econometrics. He worked the past five years in the United States fixed income market as a portfolio manager and research analyst, during which time he applied the principles of mathematics and statistics to potential investment opportunities, the pricing of bonds with embedded options and macroeconomics such as monetary policy.

Mr. Bucci currently is a part-time lecturer in mathematics and introductory statistics, and he hopes to continue to share his experiences and qualifications both in the classroom and in his consulting services. In general, Mr. Bucci can assist clients in all phases of their dissertation and/or data analysis projects, particularly in the understanding of basic probability and statistics concepts including:

• measures of central tendency and variation;
• counting rules and probability distributions;
• the Central Limit Theorem;
• confidence intervals, simple hypothesis testing and ANOVA;
• correlation and regression analysis.

For those clients specializing in mathematical finance, he can further assist in:

• Econometrics
• Times Series Analysis
• Modern Portfolio Theory
• Black-Scholes-Merton Option Pricing Theory (stocks and bonds)
• Interest Rate Modeling

Mr. Bucci enjoys working with all types of datasets and the various forms they come in. He is highly proficient with scripting and data analysis in R and Microsoft Excel, and he also has experience working with: STATA, SAS, Matlab and Minitab.

Additional Information >>

---

[an error occurred while processing this directive]

---

TOM GRANOFF
Social Science Statistics - Data Analysis - psychology

Scope: multivariate statistics, behavioral sciences, data processing, marketing research, forensic psychology, research design, SPSS, survey research, medical research, web-based surveys, quantitative methods, focus groups, interviewing techniques, qualitative methods, correlational analysis, research methodologist, ANOVA, MANOVA, logistic regression, multiple regression, discriminant function analysis, factor analysis, Method's Chapter editing, Final Oral examination preparation.

TOM GRANOFF, Ph.D., has spent almost 30 years providing research methodological and data analysis support in academic settings using SPSS. Tom typically works on numerous scholarly projects each year. Tom assists students who are obtaining advanced degrees in psychology, counseling, education, public health, leadership, business, marketing, sociology, management, and nursing. He also worked for many years in marketing research and data processing positions in the health care industry. A popular instructor, Dr. Granoff teaches graduate-level research methods and statistics courses for Loyola Marymount University, Pepperdine University, and California State University, Long Beach, all in Los Angeles. He prides himself in being able to explain most multivariate statistical tests in simple English without using complex mathematical formulas. Tom educates his clients so that they car take full responsibility for the contents of their study, and assists them in preparing for their oral defense.  His formal education includes a Ph.D. in Clinical Psychology plus Master's degrees in Theology and Industrial/Organizational Psychology.
For research proposals (Methods Chapter), Tom provides technical assistance in the following ways: helping set up the research design, reviewing surveys, assistance in selecting appropriate statistical tests, helping determine needed sample sizes (power analyses), helping develop operational definitions; developing hypotheses/research questions; measuring constructs; and tutoring students in the understanding and usage of appropriate research and statistical terminology.  Tom often edits the Methodology Chapter to ensure that the purpose statement, research questions, the hypotheses, the data gathered, and the statistical approaches are in accord.  
For data analysis projects (Results Chapter), Tom’s provides ethical assistance that does not conflict with your university’s plagiarism and academic integrity policies.  Tom will first have a brief free consultation with the student’s thesis/dissertation advisor and gain the appropriate permission before any formal work is conducted.  After securing written permission, Tom can provide any of the following services: create suitable SPSS files, help prepare the dataset for analysis, run relevant statistical tests or teach the student how to do it themselves, provide tutoring in the interpretation of SPSS output, and provide generic examples of how SPSS output could be transformed into APA style tables and narrative.  After the student has the draft of the Results Chapter, Tom can then provide technical editing to ensure the findings are presented in a clear, accurate and compelling manner.    

Additional Information >>

---

Dr. Sarah H.

STATISTICAL GENETICIST
Quantitative Genetics
Genetic Epidemiology
Genotypic and Haplotype Tests
Hardy-Weinberg equilibrium
Genome-Wide Association Studies
Golden Helix
R Statistics – R Programming

Dr. Sara H. specializes in the analysis of genetic, biological, experimental, and clinical data. She is accomplished in the areas of statistical genetics, quantitative genetics, bioinformatics and biostatistics. Dr. Sara H. was trained in mathematics and biology (BA), statistics (MA), and genetics (Ph.D.). She worked as a statistical geneticist for The Rockefeller University in the Laboratory of Statistical Genetics, with Allan Award winner Dr. Jurg Ott. She works with researchers and clinicians from Baylor College of Medicine, Rockefeller University, and Casey Eye Institute.

For medical researchers and clinicians …
She crafts statistical analyses targeted to specific hypotheses and determines which statistics would best be applied to the biological questions. Working with a variety of scientists, she has contributed to the publication of over 35 peer-reviewed publications and research abstracts within the last five years. She has publications within the areas of heart disease, age-related macular degeneration, and drug addiction.

For graduate students in biology, genetics, bioinformatics, and biostatistics …
Sara teaches basic statistics courses as well as statistics courses specific to human genetics, and was formally trained as a statistical geneticist. As a statistical geneticist in a department of primarily molecular biologists, she developed an ability to communicate complex mathematical concepts clearly to both students and fellow scientists. With her combined training in both genetic epidemiology and statistical genetics, she has expertise in analyzing genetic data. Her Ph.D. thesis explored the role of context dependency and interaction in human genetics.

Summary …
She helps select and/or perform the proper statistical analyses for genetic, biological, and clinical data. She helps develop meaningful hypotheses with statistical analyses that reflect the biological questions being asked. She recognizes issues specific to biological and genetic data and understands how they may influence statistical analyses. As a medical communications consultant, she helps communicate research results in publications, presentations, and posters. Her purpose is not just to produce results, but to relate them understandably. She assists in the design of research studies or--if the research design is complete--performs the data analyses. She will work with you throughout the process to ensure that your questions are answered. She will either assist you in doing your own analyses or perform the analyses for you with a written report of the results. She has experience in writing grants, papers and presentations, both as a supporting statistician and as a first author. She also has experience teaching statistics and statistical genetics, and is available to provide consultation and statistical support to trainees on research projects. She can assist you in documenting the statistical methods used in the data analysis, in producing clean and comprehensible graphs and tables, in preparing bibliographic entries relevant to the statistical analysis, and in manuscript content drafting and review.
Sara H. also has expertise in both observational data (cross-sectional and longitudinal studies of patients and population studies of individuals) and experimental data (rats, mice, cell lines). Sara can help with issues such as linkage disequilibrium, inter-relatedness, and context-dependent effects.

Areas of advanced expertise: programming in R, genetic analysis of related individuals (e.g., generalized estimating equations, family-based association tests), genetic analysis of unrelated individuals (e.g., t-tests, analysis of variance, chi-square tests, logistic regression, genotypic and haplotype tests, Genome-wide association studies (GWAS), next generation sequencing analysis, interaction analyses (GXG, GXE, EXE)), and fitting data to the underlying assumptions (e.g., linkage disequilibrium, Hardy-Weinberg equilibrium, tests of normality, transformation of data), as well as traditional statistical analyses including, but not limited to, ANOVA, longitudinal analysis, survival analysis, linear regression, meta-analysis, power analysis, permutation testing, and various methods of correction for multiple testing.

All analyses are performed in R or using statistical genetics software such as Golden Helix. This allows her to deal with the large amounts of data being produced in the area of genetics, such as the million marker chips.

Additional information >>

---

RONALD B. MARKS, PhD
Statistics - Data Analysis - Market Research

Ronald B. Marks, PhD was a marketing professor, now retired from the University of Wisconsin. He received his Ph.D. from the University of Missouri - Columbia, with a major in Marketing and minor in statistics. During his thirty year career, he taught undergraduate and graduate market research and multivariate statistics amongst other courses. He made extensive usage of SPSS, Minitab, and LISREL in both teaching and research. His research credentials in the use of multivariate statistics are evidenced in articles, such as: "A Structural Equation Model of Predictors for Effective Online Learning," Journal of Management Education, 29 (4), August, 2005 and "Psychometric Evaluation of the ADAPTS Scale," Journal of Personal Selling and Sales Management, Vol. XVI (4) (Fall, 1996, 53-56)

He attended seminars in "Multivariate Statistics" at the University of Colorado and "General Structural Equation ("Lisrel") Models," (Introduction and Advanced) at the Inter University Consortium for Political and Social Research, University of Michigan, Ann Arbor. He also conducted similar faculty seminars in Multivariate Statistics at the University of Wisconsin.

In counseling dissertation students and business clients, his experience is that "a problem well defined is half solved." Or as Tom Peters suggested in his best-selling book on management, "if you don't know where you are going, you are likely to end up somewhere else." That is, no matter how arcane the statistics employed, they will never compensate for poorly stated hypotheses and literature review. Hence, when consulting with students, he helps them first develop lucid, operational hypotheses and then determines which statistical methods to use, rather than the converse.

Scope: multivariate statistics, behavioral sciences, marketing research, research design, SPSS, Minitab, structural equation modeling (LISREL), survey research, web-based surveys, quantitative methods, correlation, ANOVA, MANOVA, multiple regression, discriminant analysis, factor analysis, methodology chapter editing, nonparametric tests (such as chi-square or Mann-Whitney U Test), statistical application to social science data (e.g. psychology, sociology, economics) and business data (e.g. finance, business, and marketing), can aid with set-up of data files, analysis of sample characteristics, can also help develop persuasive Power Point presentations for oral defenses or business presentations.

Additional Information >>

---

[an error occurred while processing this directive]

---

ELIZABETH L. PEARMAN
Educational Psychology - Statistics - Measurement

ELIZABETH L. PEARMAN, Ph.D. has spent more than 17 years designing surveys, analyzing data using SAS and SPSS, programming SAS and SPSS, developing assessments for unique situations, research design, developing sampling frames, calculating sample size, program evaluation, qualitative design, and qualitative analysis. Along with being an independent consultant in program evaluation, she teaches graduate classes Master's and Doctoral level research methods, qualitative methods, program evaluation, statistical programming, and lifespan development at the University of Northern Colorado for the Department of Applied Statistics and Research Methods and the Department of Educational Psychology. Elizabeth has completed over 40 program evaluations for clients, made more than 40 presentations at national conferences, published articles in several different fields, and authored three books. She has served on 25 dissertation committees and has consulted with another 40+ doctoral students on design, statistics, statistical programming, conceptualization, and writing in fields diverse as: sports administration, special education, educational leadership, human rehabilitation, educational psychology, applied statistics, school psychology, music education, chemistry education, biology education, instructional technology, psychology, reading, early childhood, and others. Her formal education includes a B.M. from the University of Missouri at Kansas City, an M.A. and Ph.D. from the University of Northern Colorado in Educational Psychology specializing in research methods, measurement/assessment, program evaluation and statistics.

Additional Information >>

---

[an error occurred while processing this directive]

---

[an error occurred while processing this directive]

---