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Research Methods

Data from this study came from the "National Women's Study-Replication." The sample of 3,001 women was formed from two U.S. population samples: a national cross-section of 2,001 women aged 18-34 years plus a national cross-section of 1,000 women aged 35 and older. Weights were created and used for all analyses with this sample to maximize representativeness by bringing the distribution of sample demographics in line with 2005 U.S. Census figures. The resulting sample consisted of 3,001 women (aged 18 to 86 years), with a mean age of 46.58 ± 17.87. We used random-digit-dial (RDD) methodology involving three steps. First, the sample was geographically stratified with sample allocation proportionate to population distribution. Second, a sample of assigned telephone banks was randomly selected from an enumeration of the Working Residential Hundreds Block (defined as each block of 100 potential telephone numbers with an exchange that includes one or more residential listings) within the active telephone exchanges within the strata. Third, a two-digit number was randomly generated by computer for each Working Residential Hundreds Block. All interviews were conducted between January 23 and June 26, 2006.

What type of sampling was this study? What is your analysis of this approach? What are the advantages and disadvantages of this approach?

The response addresses the queries posted in 550 words with references.

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The response addresses the queries posted in 550 words with references.

//The following paper is developed to find out the type of sampling used in the study and its rationale. In the first paragraph, the sampling type is identified followed by the analysis of the approach. The reasons for adopting this approach and why it is most appropriate for the study are described. At the end of the paper, the advantages and disadvantages of the identified study- Stratified Random Sampling, are discussed.//

In the research study, stratified random sampling is applied to restrict the study to the age groups that are 'less extreme' so that efficiency can be maximized and the errors in estimation can be minimized. The sample is stratified in a way that wide variety of population is represented. The population is divided into subgroups, called strata, and from each stratum, sample of pre specified size is selected on random basis (Stratified random sampling, 2010).

In this ...

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The response addresses the queries posted in 550 words with references.