Integrative Statistics

Roland B. Stark, M.Ed.
Statistician and Research Consultant

Project Details

Health Care | Education | Business | Smaller-Scale Projects | Homepage

Health Care

Understanding bullying among nurses and its implications for staff turnover

For a Ph.D. dissertation, a nurse-researcher had surveyed 500 nurses to learn about ways in which they might have been mistreated by fellow nurses; how these harmful behaviors might have related to one another; and how such mistreatment, combined with demographic factors, might explain some nurses' intention to leave the profession. Item distributions were heavily skewed, and so we searched for effective power transformations to make the variables more amenable to modeling. With this accomplished, I guided her through a series of factor analyses that helped sort two dozen behaviors into four underlying factors (roughly: punishment, belittling, exclusion, and undermining). We used these factors in multiple regression and analysis of covariance models to explain the outcome of intention to leave the profession, after generating and thoroughly checking diagnostic statistics and graphs to see whether the strength or direction of any relationships hinged on gender, ethnicity, experience, or nursing specialty. I advised and supported her as she wrote up her findings, interpreted their larger significance, and underwent a successful Ph.D. defense.

The research resulted in the publication of two articles in peer-reviewed journals, the latter article exploring the most valid and efficient ways of determining the extent to which bullying affects an organization. A new instrument comprised of just four survey items was found to be superior to a popular one that required 22. Through the first two years after publication we have fielded over a dozen requests by other researchers asking for permission to use our instrument in their research.

Explaining the incidence of surgical errors

A researcher working with a national nursing organization forged the opportunity to collect a wealth of data on the occurrence of wrong-site surgeries (e.g., removal of the wrong kidney) as well as on staffing, staff education, and climate in several hundred US hospitals. She sought to assemble these many types of objective and subjective data into a model that could help predict incidence of these catastrophic errors. Because such errors are rare given the vast number of surgeries performed, standard linear regression would have been ineffectual. I helped her devise a more general linear model -- a logistic regression model -- that was more sensitive to distinctions between the rare and the extremely rare. I also advised on scale development (combining survey responses into scale scores for greatest validity and reliability) and on model specification (maximizing the model's stability and sensitivity by choosing the most promising variables and the best number of variables to include).


Investigating faculty and staff qualifications

A consortium of over 100 private schools needed to inventory the qualifications of several thousand employees. Results would be used to support a statewide staffing initiative. I worked with the organization's leadership to devise a systematic, highly defensible strategy for coding key information from over 2,000 program documents completed each year. These documents were not standardized; they were completed by several dozen school administrators using different reporting formats and guidelines. Extracting the relevant information required a nontrivial amount of subjective decisionmaking, which undercut the precision desired for this high-stakes evaluation. I compensated by creating a Monte Carlo simulation to model the ways in which 10 types of error might have biased the estimates obtained and to show how these estimates could be corrected. As a result of this study, the organization was able to present stakeholders, including the state legislature, with better-supported, more authoritative statements on a vital topic. The study helped enable many member schools to successfully negotiate with the state for better staff compensation.

Seven additional iterations of study. In seven subsequent years I have created reports both on qualifications and on retention/turnover. My analyses have included data graphics illustrating job movement patterns typifying employees with particular characteristics and circumstances. I have also expanded the use of simulations so as to investigate longitudinal changes in qualifications and retention, since conventional statistical tests would not apply. Results have been used by the central organization as well as by many of its member schools. For this association I have also designed studies and/or conducted analyses on demographic trends likely to affect enrollment and on outcomes for students in private as opposed to public special education programs.

Understanding university enrollment

A large Mid-Atlantic university needed analytical assistance to uncover factors affecting accepted students' decisions as to whether to enroll. The university's admitted pool was unusually "price-insensitive," meaning that the size of financial aid awards had surprisingly little connection to matriculation decisions. I have used logistic regression interaction analyses, among others, to search out "pockets of price sensitivity"--subgroups for whom the award mattered more and for whom the university would thus have more leverage in using aid to attract certain kinds of students. The university has contracted with me on multiple occasions to explore issues affecting undergraduate and graduate populations, students at risk of academic probation, and international students. The work has influenced a $45-million awarding process and has filled an important gap in this enrollment management operation.

Comparing student achievement in charter schools and conventional public schools

A Ph.D. researcher in education sought to evaluate the proliferation of charter schools by analyzing the state assessment scores of all Massachusetts charter and conventional schools. An important goal was to control for socioeconomic factors -- some at the school level, which is commonly done and sometimes sufficient, but also some at the individual student level. This task was highly complicated by the nature of charter school enrollments, with a given school accepting children from as many as 20 different towns or regional districts. It was also complicated by having different sets of students and student characteristics involved in the analysis depending on grade level and subject.

We devised a complex process by which students' income levels would be estimated based on their home district, with each charter school and each conventional public district assigned SES covariates that were weighted composites of students' backgrounds. (We later found that our method was essentially the same as one developed independently by a research unit of the Massachusetts Department of Education.) In addition to helping with design and analysis for this study, I advised on manuscript editing and other aspects of the process, helping bring about a successful doctoral defense.


Surveying the US market for staff development trainings

A firm offering staff trainings and instructional materials wanted to make the most of an online survey to be sent to 20,000 professionals. I helped their marketing director formulate questions so as to obtain the clearest and most useful information, and I set up the survey using an online tool. There were dozens of analytic topics of interest to the firm; I designed a set of multivariate statistical procedures that each allowed investigation into several topics simultaneously. These linear and logistic regressions saved time and money compared to one-by-one investigation, and they had the added advantage of providing control for potentially confounding variables.

Devising a sampling plan to reduce corporate auditing expenses

An international manufacturer of agricultural equipment had hired a financial services firm for advice on how to save money on a tax audit. Of many thousands of transactions possibly eligible for tax deductions, the firm needed to identify samples that could be audited, since checking each transaction for possible deductions would have been completely cost-prohibitive. I used IRS guidelines, empirical characteristics of the body of transactions, and inferred characteristics (from a Monte Carlo simulation I designed) to help the firm make informed recommendations to their client on how to create the most advantageous samples.

Smaller-scale projects

Helping attorneys prepare rebuttal of expert testimony

In a felony trial, the state's expert witness had given extensive testimony based on a set of research findings in experimental psychology. I helped defense attorneys identify weaknesses in this expert's interpretation of these findings and their relevance to the case.

Conducting analysis for a book on developmental psychology

I helped a researcher analyze extensive data collected on sibling and family interactions. While a great deal of attention had been paid to validity of measurements, the sample size presented some problems in light of the research questions being addressed. To respond to these challenges, I found ways to improve upon the factor analysis previously conducted, and I devised ways to strategically use cluster analysis, multinomial logistic regression, and 3-D scatter plots to shed greater light on the researcher's questions. The following year the book was published by a major university press.

Data analysis in archaeology

An Ivy League archaeologist was studying artifacts found on a Greek island and dating to 2,000 to 3,000 years ago. He needed to better understand the relationships between objects, their historical periods, and the areas where they were found within the archaeological site. Initially, complex correlation matrices contributed to his understanding of these relationships. Next, several iterations of cluster analysis, conducted collaboratively, shed light on the types of objects that tended to appear together and on the profiles that might be attached to certain locations, based on the abundance of their artifacts and on the wealth and variety of trade that they indicated. All in all, the findings helped explain both the values held by these ancient peoples and the dynamics of their economies.


A committed undergraduate researcher was studying the progression of societies in ancient Mexico. Her thesis depended on her ability to distinguish between greater and lesser specialization exhibited by members of these societies, as reflected in artifacts such as potshards. I helped her evaluate several methods of comparing variabilities of different artifact measurements and to incorporate the most applicable variance tests in her dissertation.


~ Copyright 2007-2014 by Roland B. Stark. ~

"You have a gift for making the complex seem, I won't say simple, but I will say, manageable - more meaningful."

G. Burke
Doctoral student in education

"I can outline the conceptual aim of a project and know that Roland will conduct and report analyses that have a solid statistical foundation. Roland also understands that the practice of statistical analysis requires a thoughtful approach. He is skilled in building 'mindful' predictive models that take into account the possible relationships between variables, especially models involving linear and logistic regression."

University administrator

"What you wrote has been very helpful. I can't wait to cross examine this guy at trial!"

Attorney David Burgess, of
David Burgess and Associates, on my critique of opposing expert witness's testimony

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