Writing up your results

You've determined your area of interest, surveyed the literature, established hypotheses, chosen methods of testing them and collected your data. Now it's time to analyze your hard-won data and present your results.

If you wait until you finish data collection to start thinking about your analysis, you've waited too long, says Randy Larsen, PhD, head of the psychology department at Washington University in St. Louis. Rather, before you begin, establish a "road map" that matches your hypotheses to specific analyses that will best test those hypotheses, he recommends. Moreover, try to meet with your dissertation committee to go over the road map, even if your department doesn't require it.

When presenting complex relationships or numerous variables, a good chart, table or graph can make all the difference.

"You have four additional sets of eyes looking at that plan to see if it's reasonable," says Larsen.

Not having a road map--and failing to tap the resources you have--are among the common pitfalls students face in finishing their dissertations. Some students get hung up on data analysis, struggling with complex statistical procedures or wasting time on analyses that are tangential to their main research questions. Others have difficulty writing up their analyses in a clear and concise manner that meets professional standards.

The good news is that there are resources that can help you resolve such issues. From statistics workshops to style guides, such resources can help you get your dissertation done on schedule.

After all, says Larsen, "A dissertation is a project; it's got to have an end."

---

STATISTICALLY SPEAKING

One of the trickiest dissertation challenges is sorting out your data. For particularly thorny statistical challenges, the expertise you need may not be available in your home department. Karen Kaczynski, a fifth-year doctoral student at the University of Miami, began planning a dissertation on gender differences in substance abuse among inner-city Hispanic-American adolescents. Although she was familiar with longitudinal data-analysis techniques, she worried that they might not be appropriate for her small sample size of 20 female participants.

So, she attended several workshops, including the APA-sponsored Advanced Training Institute on longitudinal methods, supervised by Jack McArdle, PhD, a professor of psychology at the University of Virginia.

"I was able to ask him specifically about my concerns with using complex analytic techniques with a limited sample size," says Kaczynski. "It was really wonderful to be able to discuss my analyses with someone with his expertise." Back at her home department, she refined her analysis with the help of Maria Llabre, PhD, her department's resident statistics expert.

If you plan to continue in academia after your doctorate, delving into the details of complex statistical methods can be a wise investment, experts say. For her dissertation at Washington University, Nicole Speer, PhD, studied event perception using behavioral measures and functional brain imaging. She says that learning logistic regression, Monte Carlo simulations, brain-imaging analysis and other techniques--with the help of her adviser, other faculty members and fellow students--was well worth the effort.

"Even though it definitely ends up taking you more time to learn, in the long run it's really worth it because if you're continuing in research, you'll most likely be using similar techniques in the future," says Speer.

For computationally intensive analyses, invest in--or have access to--the hardware and software you need. Speer used an APA dissertation grant to buy a powerful computer that shaved weeks off her data analysis, she says. Even so, the analysis took three or four months longer than she had anticipated, in part because she expanded her original plans to address new questions that arose after her data were collected--a move her adviser Jeffrey Zacks, PhD, supported.

"Many data are expensive, so spending time to really digest a dataset is often a wise investment," says Zacks. As Sharon Foster, PhD, and John Cone, PhD, point out in "Dissertations and Theses From Start to Finish" (APA, 1993), adventitious findings are sometimes the most interesting ones.

At the same time, graduate students often lose valuable time exploring issues that are tangential to their main interests, says Larsen. While such meanderings can lead to real breakthroughs, graduate school may not be the ideal time to pursue them. Conduct your planned analyses, write up your results and record unexpected findings for future exploration, suggests Larsen.

---

FORMAT AND DESIGN

While the results you report may be groundbreaking, the formatting you use should be anything but. Consult style guides and follow professional guidelines, advises Stephen Hinshaw, PhD, chair of the psychology department at the University of California, Berkeley. The fifth edition of the APA Style Manual (APA, 2001) details how to prepare the results section, format text and figures, organize your dissertation, and convert it to one or more journal articles. (Check with your department for local variations from APA style.)

That said, proper formatting can only do so much. The key to good data presentation is viable, testable hypotheses, says Hinshaw. "If these are well-specified, and if a coherent data analytic plan is conceptualized and written," he explains, "the data analyses should be relatively straightforward."

When presenting complex relationships or numerous variables, a good chart, table or graph can make all the difference. For guidance on how to pick the right graphic, Zacks recommends psychologically informed books such as Stephen Kosslyn's "Elements of Graph Design" (W.H. Freeman, 1994) and William Cleveland's "The Elements of Graphing Data" (AT&T Bell Laboratories, 1994). More than just effective means of presenting your results, plots can also help you understand your own data, adds Hinshaw.

Not all psychological studies depend on quantitative measurements and statistical significance tests. For the results sections of qualitative studies, careful description and contextualization are most important, says Sue Morrow, PhD, an associate professor of counseling psychology at the University of Utah. As in quantitative studies, charts and graphs can make your results easier for readers to grasp.

Because qualitative methods tend to be less familiar to readers than quantitative methods, as well as harder to summarize with charts or statistics, one of the biggest challenges is conveying your data in a way that readers will understand. To build trust in your analysis, Morrow recommends keeping your results section separate from your discussion, as in quantitative studies, so that readers can distinguish "data-based interpretations" from your own conclusions.

---

STAY FOCUSED

While complex analyses and formatting guidelines can seem like formidable barriers to writing up your results, nonacademic factors sometimes pose even greater challenges. At this stage in your graduate career, you may have to contend with romantic breakups, family crises and the stresses of finding a job and planning a move--not to mention the ever-present temptation to procrastinate. With all of these distractions, it's important to keeping moving toward the finish line, says Larsen.

Amy L. Conrad, PhD, recently completed her doctorate in counseling psychology at the University of Iowa. When it came time to write up the results of her study on summer camps for children with cancer, she was also finishing her predoctoral internship, applying for postdocs and in her third trimester of pregnancy.

"I knew that it would be extremely difficult to get any work done after my daughter was born, and I wanted to have guilt-free time to enjoy my maternity leave," says Conrad. With the help of strict goal deadlines, constructive feedback and a lot of late-night milkshakes, she says, she finished and defended her dissertation two weeks before her daughter was born.

---

Etienne Benson is a writer in Cambridge, Mass.