Meta Analysis Reconciling the Results of Independent Studies - Research Paper Example

? Meta-Analysis Method Meta-Analysis Method Introduction Meta-analysis is a research method used in statistics, which combines the results of different studies. These studies must be independent of each other but have some resemblance. It relies on data from research studies that researchers have previously conducted. This research method mainly concerns itself with the contrasting or common features of different sets of data. Meta-analysis synthesizes different data sets into a common pool and then uses the data pool to draw conclusions and inferences (LaValley, 2010). Therefore, the method involves two distinct stages. The first stage involves identifying different data sets and summarizing the data into a uniform set. The second stage involves making conclusions from the summarized data set. Meta-analysis requires that the data is accurate and devoid of any complications. It will not be efficient if it uses inaccurate data. In addition, the method requires the analyst to identify and collect data sets from past studies, which have some aspects of resemblance in terms of the research question they address. The method is particularly effective because it draws conclusions from data characteristics rather than making generalized conclusions about data. However, the method requires planning and some level of expertise among analysts. Advantages of meta-analysis The approach defines subjective ways of checking variability of data and enables testing of all statistical parameters. Combination of different studies summarizes data and ensures the ease of drawing conclusions from the data. Other parties can also use the data to support their studies. Review of past studies eliminates unnecessary details that are insignificant to the study. Meta-analysis makes possible the prediction of the impact of significant elements of data within a specified period (Cavanaugh, 2010). Review of past studies eliminates the threat of bias sampling. It is not the opinion of the researcher that determines the similarity or difference between data sets but rather the characteristics of individual data set. This enhances the accuracy of conclusions made about data sets. Unlike other research methods, meta-analysis involves looking at the components and characteristics of variables making data from research studies rather than looking at the conclusions drawn from the previous studies. Researchers have found this method convenient in analyzing educational research. A single research on education can yield a range of different results due to a number of factors. Different research methods, the setting of the research and research instruments influence the nature of results (Allen, Bourhis, Burrell & Mabry, 2010). Therefore, there is a need to combine the different results and synthesize them into a single pool, from which it is easy to make viable conclusions. Meta-analysis is the best method that will help in meeting this data requirement. Furthermore, it summarizes data, which makes it possible for other researchers to extract useful information that may be relevant for their studies (Bernard, Abrami & Wozney, 2010). To understand this method, there is a need to look at the steps, methods and theories that govern its use. Steps followed in a meta-analysis The first step involves identifying the research problem. This includes identifying the variables and attributes that are common in different data sets. The search for relevant literature sources succeeds the first stage. This stage involves identifying sources of information from available literature reviews and other relevant studies. Meta-analysis depends on other research studies and a researcher must ensure that the results of previous studies are accurate before using them in meta-analysis. The next stage involves selecting previous studies that meet the requirements of quality and that have some resemblance in addressing the same research question. Summarization of data using appropriate methods follows this stage. Summarization standardizes data eliminating differences between different data sets that are of interest to the researcher. This stage involves identifying all aspects of homogeneity and heterogeneity between different data sets. The final stage involves using the appropriate model of reporting that is compatible with meta-analysis (Ourin, 2009). Limitations of using meta-analysis research method Failure to follow the required steps of meta-analysis results in flaws. Certain limitations arise in the way different people carry out meta-analysis (Chalmers, 2009). One of the main drawbacks of this method is that it is only applicable in studies that yield data in the form of magnitude and effect size. Quantitative researchers are the only ones who are capable of using this research method. It is impossible to use meta-analysis to analyze qualitative data. A researcher comparing qualitative and quantitative data can only use quantitative data in drawing inferences. Determining the quality of data sets depends on the researcher. There is no standard way of determining the quality of data set to be used in meta-analysis. If a researcher uses low quality data, the overall results of meta-analysis will be false and misguided (Cook, Heath, & Thompson, 2012). Publication bias affects meta-analysis. Publication bias is a concept that refers to the way people publish relevant studies and leave out the irrelevant ones. Meta-analysis should analyze all studies conducted on topics without laying emphasis on their significance and relevance. In addition, it is exceedingly difficult to identify past studies that have common characteristics. It results in researchers using studies that have almost similar characteristics, which compromises the quality of conclusions (Liberati, 2009). One of the requirements of the method is that the researcher uses at least 15 sources to make his or her conclusions. It is extremely difficult to find 15 sources that have common characteristics. Uses of meta-analysis research method in the academic literature Most scholars write articles based on a variety of research studies. They use materials from different research studies that are of relevance to the topic they are willing to discuss. Meta-analysis becomes a necessary tool in combining the results of different research studies (Dellana, Collins & West, 2012). However, application of meta-analysis depends on the research topic. Not all academic fields can apply this method because it is only applicable to quantitative research studies. Most of the academic literature that uses meta-analysis is articles on health. Many articles written by scholars on different issues concerning the health sector apply this research method. The main reason why this method is applicable in the health sector is different clinical records that are available in different health institutions. It is feasible in areas where performing clinical research through trials is unethical or difficult to achieve. This is because meta-analysis does not involve direct trials and experiments but rather uses details of other research studies (Villar, Mackey, Carroli, & Donner, A. (2010). It requires less effort than the one required in other research methods. However, the method needs careful planning and management to avoid the drawing inaccurate conclusions. Clinical charts and records differ from one patient to the other and in different institutions. Students and other academic professionals use this method to write articles about different aspects of the health sector. The process requires a careful review of all the records that have some significance in their study (Lemura, Von-Duvillard, & Mookerjee, 2008). It is a long process that involves locating relevant records and then obtaining data from these records. A review of these records eliminates the inaccurate ones that cannot be used. The researcher may use data from other secondary sources while reviewing these records. For instance, one can use data from other hospitals or use government data, which has some significance to the health records that are of interest to the study. Meta-analysis helps the researcher summarize the available records as well as explain the differences between two sets of data. Patient records will always display some similarity even if they originate from different health institutions (McAlindon, Lavalley & Gulin, 2009). Application of meta-analysis in business management context The management of business organizations can use this method to identify the effect of some variables on the performance of the organization. For instance, the organization may be interested in knowing the effect of competition and marketing strategies on its overall performance (Davis, 2010). It is difficult and expensive for an organization to carry out an independent research to value the effect of the above factors. Therefore, the best option for the organization is to rely on available research studies by other organizations. Meta-analysis is the best method for making conclusions about different sets of data (Chalmers & Haynes, 2011). Current business scene involves meeting the demands of all stakeholders from employees to customers and other interested parties. Business organizations engage in various activities meant to evaluate the level of satisfaction that individual parties get from their services. It implies that organizations must collect information from all stakeholders and then use the information to make sound decisions. Different people will have different views and the organization must summarize the views and make conclusions from the views. Making conclusions from different sets of data calls the need of using meta-analysis. Meta-analysis provides a systematic way of decision making for different organizations and individuals. Use of meta-analysis enables them identify flaws in operations which triggers the need for corrective action (Donaldson & Lee, 2008). The method offers statisticians an opportunity to manipulate formulas to make inferences from data sets. For example, the combination of regression and meta-analysis helps statisticians to study the effect of different data variables. The method is replacing previous methods of data comparing of different data. Meta-analysis is a valuable method that will benefit researchers and users of research information. However, the importance and help of this method depends on whether the researcher applies the principles that govern its use. References Allen, M., Bourhis, J., Burrell, N., & Mabry, E. (2010). Comparing student satisfac­tion with distance education to traditional classrooms in higher education: A meta­analysis. American Journal of Distance Education, 16(2), 83-97. Bernard, M., Abrami, P., & Wozney, et al. (2010). How does distance education compare with classroom instruction?  A meta-analysis of the empirical literature. Review of Educational Research, 74(3) 379-439 Cavanaugh, C. S. (2010). The effectiveness of interactive distance education tech­nologies in IK-12 learning: A meta-analysis. International Journal of Educational Telecommunications, 7, 73-88. Chalmers, T. (2009).Problems induced by meta-analyses. Stat Med, 10:971-979. Chalmers, T., & Haynes, B. (2011) Reporting, updating and correcting systematic reviews of effects of health care. BrMedJ, 309: 862-865. 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