Draws on a content analysis of methods and design from 232 articles using combined methods. Examine and discusses the rationales provide for employing mixed-methods and whether they correspond to actual practice.

Mixed-method and experimental data on working poor families and children with troubles participating in the New Hope anti-poverty experimental initiative in Milwaukee are described. Sixty percent of these families had at least one child who had significant problems (learning, school achievement and/or behavior, home behavior, retardation, other disabilities). Control group families with children who had troubles had more difficulties in sustaining their family routine than did New Hope experimental families.

During the 1990s, growing demands to end chronic welfare dependency culminated in the 1996 federal “welfare-to-work” reforms. But regardless of welfare reform, the United States has always been home to a large population of working poor—people who remain poor even when they work and do not receive welfare. In a concentrated effort to address the problems of the working poor, a coalition of community activists and business leaders in Milwaukee, Wisconsin, launched New Hope, an experimental program that boosted employment among the city’s poor while reducing poverty and improving children’s lives. In Higher Ground, Greg Duncan, Aletha Huston, and Thomas Weisner provide a compelling look at how New Hope can serve as a model for national anti-poverty policies via their qualitative, quantitative, and mixed method research approaches. New Hope was a social contract—not a welfare program—in which participants were required to work a minimum of thirty hours a week in order to be eligible for earnings supplements and health and child care subsidies. All participants had access to career counseling and temporary community service jobs. Drawing on evidence from surveys, public records of employment and earnings, in-depth interviews, and ethnographic observation, Higher Ground tells the story of this ambitious three-year social experiment and evaluates how participants fared relative to a control group. The results were highly encouraging. Poverty rates declined among families that participated in the program. Employment and earnings increased among participants who were not initially working full-time, relative to their counterparts in a control group. For those who had faced just one significant barrier to employment (such as a lack of access to child care or a spotty employment history), these gains lasted years after the program ended. Increased income, combined with New Hope’s subsidies for child care and health care, brought marked improvements to the well-being and development of participants’ children. Enrollment in child care centers increased, and fewer medical needs went unmet. Children performed better in school and exhibited fewer behavioral problems, and gains were particularly dramatic for boys, who are at the greatest risk for poor academic performance and behavioral disorders. As America takes stock of the successes and shortcomings of the Clinton-era welfare reforms, the authors convincingly demonstrate why New Hope could be a model for state and national policies to assist the working poor. Evidence based and insightfully written, Higher Ground illuminates how policymakers can make work pay for families struggling to escape poverty.

Discusses mixed methods sampling techniques in creative and effective ways.

The use of qualitative data analysis software has been increasing in recent years. A number of qualitative researchers have raised questions concerning the effect of such software in the research process. Fears have been expressed that the use of the computer for qualitative analysis may interfere with the relationship between the researcher and the research process itself by distancing the researcher from both the data and the respondent. Others have suggested that the use of a quantitative tool, the computer, would lead to data dredging, quantification of results, and loss of the "art" of qualitative analysis. In this study of 12 qualitative researchers, including both faculty members and graduate students, we have found that these fears are exaggerated. Users of qualitative data analysis software in most cases use the computer as an organizational, time-saving tool and take special care to maintain close relationships with both the data and the respondents. It is an open question, however, whether or not the amount of time and effort saved by the computer enhance research creativity. The research findings are mixed in this area. At issue is the distinction between creativity and productivity when computer methods are used. Computer packages targeted at qualitative and mixed methods research data are readily available and the methodology sections of research articles indicate that they are being utilised by some health researchers. The purpose of this article is to draw together concerns which have been expressed by researchers and critics and to place these within the perspective of 'framing' (MacLachlan & Reid, 1994). Here, the focus becomes the frame that these computer programs impose on qualitative data. Inevitably, all data sets are disturbed by the techniques of collection and the conceptual and theoretical frames imposed, but computer framing not only distorts physically but also imposes an often minimally acknowledged frame constructed by the metaphors and implicit ideology of the program. This frame is in opposition to most of the recent changes in qualitative data interpretation, which have emphasized context, thick description and exposure of the minimally disturbed voices of participants.

How do you decide whether to use a qualitative or a quantitative approach for the design of a research study? How do you write up the results of a study for a scholarly journal article or dissertation? This book addresses these issues by providing a guide to major design decisions, such as deciding a paradigm, stating a purpose for the study, identifying the research questions and hypotheses, using theory, and defining and stating the significance of the study. Research Design is aimed at upper division to graduate level research methods courses that are taught to prepare students to plan and write up independent research studies. In the past two decades, research approaches have multiplied to a point at which investigators or inquirers have many choices. For those designing a proposal or plan, I recommend that a general framework be adopted to provide guidance about all facets of the study, from assessing the general philosophical ideas behind the inquiry to the detailed data collection and analysis procedures. Using an extant framework also allows researchers to lodge their plans in ideas well grounded in the literature and recognized by audiences (e.g., faculty committees) that read and support proposals for research. What frameworks exist for designing a proposal? Although different types and terms abound In the literature, I will focus on three: quantitative, qualitative, and mixed methods approaches. 'The first has been available to the social and human scientist for years, the second has emerged primarily during the last three or four decades, and the last is new and still developing in form and substance. This chapter introduces the reader to the three approaches to research. I suggest that to understand them, the proposal developer needs to consider three framework elements: philosophical assumptions about what constitutes knowledge claims; general procedures of research called strategies of inquhy and detailed procedures of data collection, analysis, and writing. called methods. Qualitative, quantitative, and mixed methods approaches frame each of these elements differently, and these defiances are identified and discussed in this chapter. 'Then typical scenarios that combine the three elements are advanced, followed by the reasons why one would choose one approach over another in designing a study. 'This discussion will not be a philosophical treatise on the nature of knowledge, but it will provide a practical grounding in some of the philosophical ideas behind research.

Written by a long-time authority on focus group, presents a brief history of focus group application up to, and including, information on the variety of current uses across many disciplines. Great section on the uses of focus groups in combination with other methods with a full compare/contrast discussion. Finally, goes into the specifics on ‘how to’ plan and conduct effective group data collection. My own preference (Morgan, 1996) is for a more inclusive approach that broadly defines focus groups as a research technique that collects data through group interaction on a topic determined by the researcher. In essence, it is the researcher's interest that provides the focus, whereas the data themselves come from the group interaction. One reason for favoring an inclusive approach is that the exclusive approaches do not really exclude very much. Other than focus groups, the primary categories of group interviews in the existing typologies are things that are manifestly different from focus groups. On the one hand, there are nominal groups and Delphi groups (Stewart & Shamdasani, 1990), which do not involve actual group interaction. On the other hand, there is the observation of naturally occurring groups, which typically do not involve the researcher in determining the topic of discussion. Thus, little is gained by excluding these categories of data collection because they already fall outside the broad definition of focus groups offered here. Among the more specific criteria that could be used to distinguish focus groups from other types of group interviews, both Frey and Fontana (1989) and Khan and Manderson (1992) assert that focus groups are more formal. In particular, they argue that focus groups are likely to involve inviting participants to the discussion and they also stress the distinctive role of the moderator. Although there is no doubt that group interviews vary along a continuum from more formally structured interaction to more informal gatherings, I do not believe it is possible to draw a line between formal and informal group interviews in a way that defines some as focus groups and others as something else. Instead, I find it more useful to think that the degree of formal structure in a focus group is a decision that the research makes according to the specific purposes of the research project. In particular, the use of either a more formal or a less formal approach will depend on the researcher's goals, the nature of the research setting, and the likely reaction of the participants to the research topic. Among the other criteria that have been offered as distinguishing features of focus groups are their size and the use of specialized facilities for the interview (McQuarrie, 1996). Again, however, these supposedly exclusive criteria are mostly a matter of degree. Who is to say when a group is too large or too small to be called a focus group or when a setting is too casual to qualify? Rather than generate pointless debates about what is or is not a focus group, I prefer to treat focus groups as a "broad umbrella" or "big tent" that can include many different variations. Of course, this approach requires researchers to make choices about doing focus groups one way rather than another. Fortunately, this need to make explicit decisions about data collection strategies is a familiar concern to social scientists, and it comes under the heading of "research design." As social scientists have gained increasing experience with focus groups, we also have produced insights into the situations in which different research designs are either more or less likely to be effective (e.g., Krueger, 1993; Morgan, 1992.a, 1995).

Discusses issues, types, and calculations for inter-rater reliability. Seventeen measures of association for observer reliability (interobserver agreement) are reviewed and computational formulas are given in a common notational system. An empirical comparison of 10 of these measures is made over a range of potential reliability check results.

Low-skilled women in the 1990s took widely different paths in trying to support their children. Some held good jobs with growth potential, some cycled in and out of low-paying jobs, some worked part time, and others stayed out of the labor force entirely. Scholars have closely analyzed the economic consequences of these varied trajectories, but little qualitative or mixed method research has focused on the consequences of a mother’s career path on her children’s development. Making It Work, edited by Hirokazu Yoshikawa, Thomas Weisner, and Edward Lowe, looks past the economic statistics to illustrate how different employment trajectories affect the social and emotional lives of poor women and their children. Making It Work examines Milwaukee’s New Hope program, an experiment testing the effectiveness of an anti-poverty initiative that provided health and child care subsidies, wage supplements, and other services to full-time low-wage workers. Employing parent surveys, teacher reports, child assessment measures, ethnographic studies, and state administrative records, Making It Work provides a detailed picture of how a mother’s work trajectory affects her, her family, and her children’s school performance, social behavior, and expectations for the future. Rashmita Mistry and Edward D. Lowe find that increases in a mother’s income were linked to higher school performance in her children. Without large financial worries, mothers gained extra confidence in their ability to parent, which translated into better test scores and higher teacher appraisals for their children. JoAnn Hsueh finds that the children of women with erratic work schedules and non-standard hours—conditions endemic to the low-skilled labor market—exhibited higher levels of anxiety and depression. Conversely, Noemi Enchautegui-de-Jesus, Hirokazu Yoshikawa, and Vonnie McLoyd discover that better job quality predicted lower levels of acting-out and withdrawal among children. Perhaps most surprisingly, Anna Gassman-Pines, Hirokazu Yoshikawa, and Sandra Nay note that as wages for these workers rose, so did their marriage rates, suggesting that those worried about family values should also be concerned with alleviating poverty in America. It is too simplistic to say that parental work is either “good” or “bad” for children. Making It Work gives a nuanced view of how job quality, flexibility, and wages are of the utmost importance for the well-being of low-income parents and children.Looks past the economic statistics to illustrate how different employment trajectories affect the social and emotional lives of poor women and their children.

Introduces and traces the history of the methodological paradigm wars and brings readers up to the state of affairs (albeit, 1998). Discuss the ‘warring’ positions and the evolution of thinking regarding pragmatism and the development of mixed methods approaches to social science research.