**2. Methodology of meta-analysis**

The results of a single study can be influenced by characteristics of the study setting, the sampled population, timing, locations and the subjective bias of the researchers. Causal factors of certain effects can only be unearthed by a synthesis of multiple studies rather than a single study. Some general trends and underlying principles can only be deduced across a large body of case studies or empirical studies. Therefore, since its very beginning, the methodology of meta-analysis is expected to be such a solution to synthesize amount of studies and get to the essences of problems with as least as possible bias.

Beecher (1995) undertook the earliest example of a meta-analysis and Glass (1976) coined the term "meta-analysis" to refer to a philosophy, not a statistical technique. The meta-analysis method began as a statistical procedure for combining and comparing research findings from different studies focusing on similar phenomena (Nijkamp and Pepping 1997-98), and a variety of meta-analytical methods have been developed in the past decades(Nijkamp 1999).

In some studies, "meta-analysis", "meta-synthesis", "synthesis review", and some other terms, are not distinguished clearly, but there are uses of the technique in various research fields. While some researchers refer to the term "meta-analysis" as the quantitative integration and analysis of the findings from all empirical studies relevant to an issue and amenable to quantitative aggregation (Glass 1976), most treat the terms "literature review", "synthesis review", "synthesis analysis" and "meta-analysis" as equivalent. Also some researchers separate "meta-summary" and "meta-synthesis". For example, in study of Sandolowski and Barroso (2003) in the field of nursing, the qualitative meta-summary is explained as involving the extraction and further abstraction of findings, and the calculation of manifest frequency effect sizes while meta-synthesis is an interpretive integration of qualitative findings that are themselves interpretive syntheses of data, including the phenomenologies, ethnographies, grounded theories, and other integrated and coherent descriptions or explanations of phenomena, events, or cases that are the hallmarks of qualitative research. (Sandelowski and Barroso 2003).

Here the definition of "meta-analysis" is simply taken as the general term of all the different nominal meta-methods, as "…an analytical framework for comparative research that aims to draw inferences on common issues with different but allied empirical backgrounds" (Matarazzo and Nijkamp 1997).

Meta-analysis has now become a widely accepted research tool, encompassing a range of procedures used in a variety of disciplines, such as medicine, nursing, psychology, labor economics, environmental science, and transportation science (Gaarder 2002; Yu 2002; Greenaway, Milne et al. 2004; Travisi, Florax et al. 2004). The wide employment of metaanalysis is partially because that it is an integration which is more than the sum of parts in that it offers novel interpretations of findings(Sandelowski and Barroso 2003). In the study of Sandolowski and Barroso(2003), they found that this kind of interpretations will not be found in any single report, but rather are inferences derived from taking all of the reports in a sample as a whole. Their validity does not reside in replication logic, but rather in inclusive logic whereby all findings are accommodated and in the craftsmanship exhibited in the final product(Sandelowski and Barroso 2003).

Under the Meta-analysis framework, appropriate methods can be selected according to different research questions. Commonly used methods include the counting method, classical Meta-analysis method, Meta-analysis on effectiveness, homogeneity testing and other methods.

1. Vote-counting

128 Sociological Landscape – Theories, Realities and Trends

Therefore, the rationale of this study is promoted by factors on both sides of methodology

• What are the pivotal methodological issues of the qualitative meta-analysis when applied? With the development of more than three decades, various frameworks have been brought out for the application of meta-analysis. Although it is widely accepted that with the basic principles, the techniques could be different according to characteristics of research fields, there are still problems of relative uncertainty. The aim of methodological is to discuss these pivotal issues with the vulnerability research as an

• What are the key driving causes to the vulnerability to natural hazards? Compared with the increase in the number of advanced research on vulnerability, in the real world people are still suffering from rising vulnerability to natural hazards. Especially with the shocks from 2004 tsunami, 2005 and 2007 hurricanes, the coastal hazards came to the attention focus. With the application of meta-analysis, the aim of research is to recognize the key factors contributing to vulnerability, and synthesize the driving

To achieve the above aims, this paper applies meta-analysis in the qualitative studies with the context of the vulnerability research questions. In the second section, the methodology of meta-analysis is introduced; in the third section, the findings of the application of metaanalysis in vulnerability research are presented; finally, in the forth section, there are the

The results of a single study can be influenced by characteristics of the study setting, the sampled population, timing, locations and the subjective bias of the researchers. Causal factors of certain effects can only be unearthed by a synthesis of multiple studies rather than a single study. Some general trends and underlying principles can only be deduced across a large body of case studies or empirical studies. Therefore, since its very beginning, the methodology of meta-analysis is expected to be such a solution to synthesize amount of

Beecher (1995) undertook the earliest example of a meta-analysis and Glass (1976) coined the term "meta-analysis" to refer to a philosophy, not a statistical technique. The meta-analysis method began as a statistical procedure for combining and comparing research findings from different studies focusing on similar phenomena (Nijkamp and Pepping 1997-98), and a variety of meta-analytical methods have been developed in the past decades(Nijkamp 1999). In some studies, "meta-analysis", "meta-synthesis", "synthesis review", and some other terms, are not distinguished clearly, but there are uses of the technique in various research fields. While some researchers refer to the term "meta-analysis" as the quantitative integration and analysis of the findings from all empirical studies relevant to an issue and amenable to quantitative aggregation (Glass 1976), most treat the terms "literature review", "synthesis review", "synthesis analysis" and "meta-analysis" as equivalent. Also some researchers separate "meta-summary" and "meta-synthesis". For example, in study of Sandolowski and Barroso (2003) in the field of nursing, the qualitative meta-summary is explained as involving the extraction and further abstraction of findings, and the calculation

discussions on both the vulnerability and the implementation of meta-analysis itself.

studies and get to the essences of problems with as least as possible bias.

and research question:

applied case.

relationship between these factors.

**2. Methodology of meta-analysis** 

This approach is similar to the narrative review, which divides the results of previous researches into three groups of significant positive results, significant negative results, and non-significant results. The result of the group with most literature number then represents the entire field of study. This method is relatively simple to determine the general trend of a large number of case studies. However, this is an inaccurate statistics which relies on the statistical significance. Also each individual study is limited by the collection of samples, so the final results of vote-counting do not necessarily reflect the true situation.

2. Classic or Glassian Meta-analysis

This approach evolves from the early Glass Meta-analysis. It defines research questions first, then collects case studies, followed by encoding the outputs of each features, and finally analyzes the relationship between the output values and the study characteristics. This method of Meta-analysis and its subsequent improved methods have three common characteristics: First, the selection criteria of literature is liberal, generally based on the research needs. Second, the units of analysis are the results of each single studies, and through selecting the appropriate sample size (ie, the number of literature)**,** the comparative analysis is taken. Third, Meta-analysis methods usually weaken the characteristics of each individual study, and present the overall average characteristics instead.

A Meta-Analysis Framework and

comprises seven steps:

strategy);

data(Sandelowski and Barroso 2003).

1. Formulation of the research questions;

analysis steps is shown in figure 1.

3. Analysis and synthesis of the theories (meta-theory); 4. Identification of an analytic strategy (meta-analysis); 5. Analysis of the methods in collected cases (meta-method); 6. Synthesis of the outputs of the above processes (meta-synthesis);

analysis level and implementation level(Matarazzo and Nijkamp 1997).

Fig. 1. The levels and corresponding steps of a meta-analysis

7. Presentation and dissemination of the findings.

Its Application for Exploring the Driving Causes to Social Vulnerability 131

Generally, Meta-analysis methods include constant comparison, taxonomic analysis, the reciprocal translation of in vivo concepts, and the use of imported concepts to frame

The mata-analysis requires the establishment of an analytic strategy and coding system to categorize data and to interpret findings in relation to predefined research questions. According to Glasmeier and Farrigan (2005) the synthesis process on qualitative research

2. Selection and appraisal of primary research (development of a literature search

The process of meta-analysis is not a linear process. 3), 4) and 5) are parallel steps that focus on different aspects of theories, contents and methodologies. Also, the various steps overlap and are circular. The development of the coding system continues throughout all stages, in order to substantiate the process and make sure that all important information is included. In this way, the coding system can be modified, revised and supplemented according to the concrete cases. Also Matarazzo and Nijkamp (1997) present the meta-study as six different "levels", each of which assumes a particular importance from a methodological point of vview. The levels are named real-world level, study level, pre-meta-analysis level, study selection level, meta-

Combining the different steps and the levels together, meta-analysis is essentially a kind of "mining" or "emerging" of integrated findings. An integrated map of undertaking meta-

Practice has proved that the classic Meta-analysis in many areas has good applicability, and is considered as "research on research" (Greenaway, Milne et al. 2004). However, this classical method has some weaknesses. The most obvious one is that because this method averages all case studies, and the differences between the various studies are ignored. Therefore the reliability of the analysis results is very susceptible to those flawed researches. In addition, if a single case study has a large sample size, it is possible that the weight given to this study is relatively large, which affects the results of the analysis.

3. Study effect meta-analysis

This method of Meta-analysis improves the classical methods on two aspects. First, the literature becomes more selective, excluding case studies which have defects in the methods and probably mislead the analysis results. Second, the method takes each individual study as the unit of analysis, rather than the results of each individual study. Thus, in essence, each individual research is given the same weight, and the results of the Meta-analysis will not be affected by sample size. However, this method will directly reduce the amount of data involved in the analysis, also the subjectivity of the researchers possibly affects the research.

4. Tests of homogeneity

The idea of homogeneity testing originated from pattern recognition. Some scholars believe that the traditional statistical test method is not suitable for Meta-analysis. The effective sample size is affected by many factors: the reliability of measurement, sampling limits, reporting errors of data processing, unreported factors, etc. Homogeneity test can effectively distinguish the nuances in different samples. If the homogeneity test is significant for a group of researches, it can be deduced that this group of researches belongs to one category. With this method, people can classified the collected large number of empirical studies, figuring out the similar characteristics of each category.

A variety of Meta-analysis methods has long been used in research field of laboratory medicine, clinical medicine and behavioral science. There are also applications in experimental or quasi-experimental studies in the economic environment (Travisi, Florax et al. 2004). For example, a New Zealand government-funded research built a framework for future implementation of very effective guidelines drawn from the Meta-analysis of 10 government aided community projects (Greenaway, Milne et al. 2004). In recent years, Meta-analysis methods began to be used in the environment and climate change related researches.
