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)

"She was wonderful. I was having difficulty putting all the information together and she just cleared things up for me. My stress level has definitely gotten better!"

"She is the best stat consultant. I could not finish my dissertation without her. She is available almost 24 hours and responded to all of my questions. She returned my work so quickly. Her explanation was always clear and accurate even though I am not good at statistics. She is so patient for explaining every detail stat question."

"Victoria was very professional and prompt in her service delivery. She had a command of the updated literature. I was very comfortable that she knew the current trends in the statistics I needed to use for my dissertation. She was extremely thorough and answered all of my questions in language I could comprehend. I would recommend Victoria to any graduate students who need help with advanced statistics for their projects."

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William Buchanan received his PhD at TUI University where his dissertation research focused on the causal effects of poverty on musical achievement in the US. He makes use of geospatial analysis (i.e., using ArcGIS software to measure resource allocation, concentration, and geographical differences in resource availability), econometrics (i.e., instrumental variable methods, regression discontinuity designs, differences-in-differences estimators, fixed-effects models, and others), and structural equation models (i.e., path analysis of observed data, latent variable modeling, etc…) to conduct quasi-experimental data analysis with a national data set from the US Department of Education. His use of multi-disciplinary approaches to research allowed him to integrate theory and statistical methodology from economics, education, and psychology.  He has also provided statistical consulting and research services to a wide variety of public school districts, businesses, and institutions of higher education.

William Buchanan is also an aspiring Stata programmer and has helped his client to automate their data analysis by providing custom written Stata programs (i.e., .do and .ado).  He also uses SPSS 16, LISREL 8.8, HLM 6.0, R, G*Power 3.2, ArcGIS, and other software packages to perform data analysis.  Additionally, he uses StatTransfer 10 and is able to accept data files in almost any format and can provide data files in the format of your choice.

Specialties: music education, developmental psychology, neuropsychology, cognitive psychology, education, education policy, program evaluation, arts integration in education, econometric methods in educational research, contextual factors in education/developmental psychology, LaTeX typesetting software.

Using Stata to Automate Summary Statistics in Longitudinal Data

What's New in Stata 12?

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Prof. Barry Collins is Emeritus Professor of Psychology at UCLA. His numerous publications cover social psychology, applied social psychology, research methods, attitude change, persuasion, and social influence, Dissonance Theory, the design and evaluation of questionnaire measures, interviewing, health education, and community-based participatory research. These publications use a wide variety of statistical analyses. He served as Director of Research at Healthy African American Families II. He has taught at Yale and Stanford and was a Prof. of Sociology at the University of Wisconsin. He has written a textbooks on social psychology and research methods. He coauthored a book on Theories of Attitude Change. He has served and chair and vice chair of the human subjects protection committee (IRB). He has been an advisor for over a hundred undergraduate honors theses and MA and PhD theses. He has served as a social-psychology expert witness in court cases. His BS and MA were in communication at Northwestern University. He has focuses on one-on-one mentoring on activities ranging from: (a) the choice of a research topic that is relevant to the interests and skills of a particular student, (b) the identification of the most relevant theories, (c) the development of hypotheses, (d) research design, (e) the organization of research writing, (f) methods sections, (g) data analyses and the presentation results, and (h) the interpretation of results.

He has frequently served as a consulting editor for the major journals in social psychology, evaluating manuscrips for potential publication.

Research Interests

• Applied Social Psychology
• Close Relationships
• Communication
• Culture/Ethnicity
• Ethics/Morality
• Health
• Interpersonal Processes
• Person Perception
• Persuasion/Social Influence
• Prejudice/Stereotyping
• Research Methods/Assessment
• Self/Identity

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Tom Granoff, Ph.D.has spent almost 30 years providing research methodological and data analysis support in academic settings using SPSS and SAS. 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 and Pepperdine University, both 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.

tomgranoff@editing-writing.com

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. 

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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.

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Dr. Vicki Lawrence is an academic researcher who studies the epidemiologic nature of social conditions in relation to cardiovascular and other disease outcomes. More specifically, her work focuses on studies of poor health among African Americans and health disparities that may occur my age, race, and gender in cardiovascular and mental health outcomes. Utilizing her background in epidemiology and biostatistics, she has provided statistical support on multiple studies with various investigators commonly focused on physical and mental health data. In addition, she has worked with clinicians, research investigators, and tutored multiple graduate students as well in public health, epidemiology, social work, medicine, education, and nursing to tackle statistics related issues.

Dr. Lawrence takes a significant amount of effort to ensure the students and researchers she collaborates with or supports understand the theoretical rationale behind the methods appropriate for their research problems, meeting the students and researchers at their stage of understanding. In addition to explaining the foundations, she regularly provides each individual has the opportunity to ask questions, and explains the differences in statistical approaches as needed. Further, she can help develop data analysis plans, refine research questions, and examine data collection methodologies with clients as well.

In her own work, Dr. Lawrence has used exploratory/ descriptive analysis tools (such as t-tests) and nonparametric tests, ANOVA (including one way, two way, repeated measures and others), structural equation modeling, exploratory factor analyses, multilevel models, linear regression, logistic regression, multinomial regression, and growth curve modeling as well. She has prepared analytical methods sections for publications, including tables of regression outputs. Further, she can provide information relevant to epidemiologic methods, including prevalence, incidence, risk and rate ratios, causal diagrams (including mediating and moderating variables) and other topics as needed. She has used a variety of data sets of both large and small magnitude, including nationally representative public data sets such as NHANES and the Panel Study of Income Dynamics, but has also used survey as well as medical systems based data. She has substantial experience using SAS and Excel, and also uses HLM and SPSS.

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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.

"Using Ron was the best decision we made about our graduate research project. While we knew the field of anesthesia, none of us were statisticians and we struggled greatly in making sense of our data. Ron simplified everything and had most of our questions answered within 48 hours of our initial request. Excellent service and quality."

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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. She has served on 25 dissertation committees and has consulted with another 40+ doctoral students on design, statistics, statistical programming, and conceptualization. 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.

Betsy can help you with all phases of your dissertation/thesis from conceptualizing the dissertation/thesis, use of qualitative methods, qualitative design, qualitative analysis or quantitative methods. Her statistical skills are extensive (descriptive, inferential, multivariate, regression analysis, factor and cluster analysis, and reliability and validity, etc.) along with expertise in survey/questionnaire design and development, methodology chapter editing, sampling techniques and sample size calculation, proposal development, defense preparation, web-based surveys, data entry, data editing, statistical programming, measurement/ assessment, data interpretation and understanding, experimental and quasi-experimental design, Internal Review Board applications, informed consent forms.

She can make statistics understandable, will help you develop and edit your methodology chapter, assist you in understanding your data, help you with formulating your research questions, and guide you from the conceptualization of your dissertation/thesis to the defense so you will learn and understand your data, results, and study.

"... after my wife and children, you come in a close second. Below are my acknowledgements and while you're listed after my committee (I felt compelled to put them at the top) you are truly the most important contributor to my work. While the statistics were a component, your help with the survey instrument leading up to the statistics really helped me bridge a gap and work toward closure. Without the instrument and the associated statistics I would have been lost and at a time when I didn't know what to do, you gave me guidance. It may not even be anything you remember but your effort on the survey really set me on the right path. For that I thank you!"

"Words can't express how instrumental you were in this process. When I sought out assistance I didn't expect someone as dedicated as you. Although my dissertation focused on the motivation of elementary students the findings had implications that suited me as well. It's always nice to be believed in. Your goal structure is definitely in the 'mastery' realm. You made me believe in myself even when there was so much doubt. I appreciate the long hours that you invested in me, not to mention, the encouraging words that often times calmed my fears. You knew exactly what to say at the right time. Your expertise is invaluable."

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M Perrin received her MPH in Epidemiology from Columbia University and is currently a doctoral candidate in neuropsychology. Ms. Perrin worked as a Lead Scientist for the NYC Department of Health and Mental Hygiene. She helped develop a large-scale public health study and created surveys for assessing the psychological and physical health of survivors of the World Trade Center disaster. Ms. Perrin also provides mentorship to graduate-level statistics interns and teaches seminars in research methods and statistics to public health professionals.

Ms. Perrin received an award from the NYC Department of Health and Mental Hygiene for the year’s most impactful journal article and was invited to present her research at community and professional meetings. She has published 12 scholarly articles and presented findings at 13 scientific conferences. Ms. Perrin has also served as an ad hoc peer reviewer for 7 high-tier scientific journals, providing critical analysis of over 20 research studies.

Ms. Perrin is a statistical consultant for principal investigators and graduate students in psychology, education, pediatric endocrinology, psychopharmacology and neuroscience. She helps clients formulate testable hypotheses, devise accurate methods of assessment and conduct appropriate statistical analyses. She also provides critical review of written statistical reports to ensure that findings are presented in a clear and organized manner.

Ms. Perrin programs in SPSS\SAS and is familiar with AMOS, Matlab and STATA. Her statistical expertise include:

1. - Sample size and power calculations
2. - Reliability analysis (ICC, Chronbach’s Alpha)
3. - Pearson\Spearman Correlation analysis, T-tests
4. - Non-parametric analyses (Chi-square, Mann Whitney, Fisher’s Exact, etc.)
5. - ANOVA, ANCOVA, RM ANOVA
6. - Logistic and linear regression (univariate and multivariate)
7. - Survival analysis (Kaplan Meier, Cox Proportional Hazard Analysis)
8. - Structural Equation Modeling\Path Analysis
9. - Exploratory and Confirmatory Factor Analysis (Principal Component, Principal Factor Analysis)
10. - Hierarchical Linear Modeling\Mixed Model Regression Analysis\Canonical Correlation Analysis

Her research interests include:

1. - neurophysiology (ERP\EEG assessments)
2. - neuropsychology (auditory and visual processing, attention, memory and executive functioning)
3. - schizophrenia
4. - anxiety disorders\posttraumatic stress disorder
5. - psychiatric epidemiology\public health\behavioral health
6. - disaster\trauma

   "You were such a pleasure to work with. You removed the anxiety by explaining things in a simplified way that I could understand! I felt confident going into my defense and was able to cogently answer questions from my committee members. I would recommend you without reservation." Virginia De Sanctis

   "I cannot thank you enough for being such a patient and knowledgeable colleague. Without your expertise and guidance in data preparation and statistical analysis, our publications would never have been so well accepted by top-tiered journals. I truly appreciate and value your skills, patience, vision, and collaborative nature!" ~ Laura DiGrande, Dr.P.H., M.P.H.

Articles:

Growth trajectory during early life and risk of adult schizophrenia

Elevated maternal Interleukin-8 levels and risk of schizophrenia in adult offspring

Posttraumatic stress symptoms, PTSD, and risk factors among lower Manhattan residents 2–3 Years after the September 11, 2001 terrorist attacks

Differences in PTSD prevalence and associated risk factors among World Trade Center disaster rescue and recovery workers

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Dr. Jane Scott approaches statistics with the same motto that she uses in life: “Keep it simple and have fun with it!” Jane received her Ph.D. in Quantitative Psychology with an emphasis on personality psychology from the University of California. She teaches statistics for psychology at S. Pacific university, where they let her wear shorts and teach barefoot. Her students often leave her class amazed that they have come to like a subject of which they were 2initially frightened.

Jane can help you analyze your data and interpret the results using SAS or SPSS. She can help you understand, implement, and interpret statistical procedures such as t-tests (single-sample t-test, independent t-test, dependent or paired t-test), ANOVAs (one-way ANOVA, two-way ANOVA, repeated measures ANOVA, mixed ANOVA, MANOVA), correlation, chi-square, multivariate procedures (multiple regression, logistic regression, factor analysis, principal component analysis or PCA), and survival analysis, among others. She can also provide simple explanations for such statistical concepts as variance, standard deviation, z-scores and the normal distribution, the central limit theorem, type-I and type-II errors (alpha and beta), power, effect size, R-squared or the coefficient of determination, and the Pearson Product Moment Correlation Coefficient, as well as concepts from psychometrics such as reliability and validity.

Jane received her bachelor’s degree in English from the University of California, Berkeley, so she spent her undergraduate years developing her writing and communication skills which enable her to communicate mathematical concepts clearly. She loves to help students hone their methodology chapters, formulate clear hypotheses, and clearly articulate the appropriate analyses for testing each hypothesis. An animated teacher and public speaker, Jane can also help you develop effective Power Point presentations for classes or oral defenses.

"Dr. Jane was terrific. She responded promptly to my queries, worked quickly and accurately. She was happy to provide options and spent as much time as necessary to see that I felt confident with the outcome."

“After consulting two previous statistical experts who failed to provide me with adequate help, Jane was truly professional and knowledgeable.” (Contact information on request)

"Jane was always exceptionally communicative, efficient, and organized. In addition, she had a strong knowledge base and ability to explain statistical procedures and concepts in user-friendly language. I couldn’t have been happier with her services and I would recommend her."

"I successfully defended my dissertation earlier today. Thanks for making this happen...your help was very instrumental in getting this far. Thanks and thanks again!"

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DJ Simons, MA, is a recent graduate of the University of North Carolina’s developmental psychology program, where he had a formal concentration in quantitative methods.  He has served as a teacher’s assistant many times, including four times for Statistics for Psychologists and twice for Research Methods for Psychology.  He has also served as a data analyst for a private education research firm, and has privately tutored undergraduate and graduate students in statistics.

DJ has aided students and colleagues through all steps of the research process, from formulating a research question and hypothesis, through data analysis, to reporting the results in a scholarly fashion using APA style. He is happy to help undergraduate and graduate students with their statistics classes, master’s theses or doctoral dissertations in the social sciences, explaining every step of the process clearly and concisely. He will make sure that you understand your data, and that you can speak intelligently on its content, use and application.

He can advise on, among other things, research methodology, ANOVA, ANCOVA, t-tests, linear, multiple and logistic regression, chi-square, factor analysis, and hierarchical linear modeling/multilevel modeling (HLM). Although his background is in quantitative psychology, he can help with statistics for other social sciences such as Sociology, Social Work and Education.  He is highly proficient with SPSS, both menu-based and syntax, and can also help with SAS, SPSS, CEFA, and R.

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