- DATA ANALYSIS WITH EXCEL DESCRIPTION 64 BIT
- DATA ANALYSIS WITH EXCEL DESCRIPTION SOFTWARE
- DATA ANALYSIS WITH EXCEL DESCRIPTION FREE
Steps 1 and 2 always require adjustments according to study type and outcome. All formulas are presented in traditional equations and also in excel format.
We chose to use theoretical numbers so we could openly distribute the spreadsheets, test particular formulas and compare results obtained with other software. The data could be the prevalence of smoking in a country or the incidence of myocardial infarction in high risk patients.
DATA ANALYSIS WITH EXCEL DESCRIPTION SOFTWARE
Since we have established that the limitation of the existing software packages is handling descriptive data, we will be using rates in our example so that the difference in the final forest plot is more overt. We will refer to both these estimates simply as "outcome" in order to avoid confusion, and maintain only the abbreviation as es to follow textbooks standard. However, some reviews may only aim in combining rates or prevalences technically these cannot be called "effects", since there is nothing "causing" it, and the correct term would be single group summary. The outcome of meta-analyses is the effect summary. The spreadsheets were later tested on Excel 2003, with no differences found in either the calculations or graphs.
DATA ANALYSIS WITH EXCEL DESCRIPTION 64 BIT
The method described here was designed on a laptop with Intel Core Duo 2.2 GHz processor, 4 GB RAM, running Windows Seven 64 bit and Microsoft Office Excel 2007.
Our work is separated into two spreadsheets, so researchers can use both to conduct all calculations or simply the second one if they have already analyzed the data in any other software, but want an appealing graphical way of presenting it. Borestein et al cites the impossibility of producing forest plots as an important limitation, but we have developed a method to turn a scatter plot into a statistically correct forest plot, allowing the researcher to take advantage of all excel formatting tools. However, if the calculations are done in steps, statistics like Q and I 2 can be computed with basic arithmetic operations. Most researchers would be uncomfortable entering all the formulas themselves, since they may seem complex at first. Although it has a purchase cost, it is usually already installed in most computers, bundled with Microsoft Office package. Īnother option would be to analyze data using directly Microsoft Excel. Some other options are no longer available, as FAST*PRO, and others are still currently under development, as Meta-Analyst.
DATA ANALYSIS WITH EXCEL DESCRIPTION FREE
It can be used for analysis of descriptive data selecting the input type to "continuous", but the free version does not allow for analysis of original data, only build in datasets. Finally, there is also Meta-Analysis Made Easy (MIX), an add-on for Excel. It can perform advanced analyses, but there are still limitations regarding graphic display, particularly of descriptive data, since CMA does not allow customization of the forest plot produced. The former only accepts three types of primary data, while the latter has a purchase cost, but accepts more types of data. Metawin and Comprehensive Metanalysis (CMA) are commercial software that have user friendly interfaces. It only accepts effect sizes in traditional formats. RevMan is a freeware program from the Cochrane Collaboration that requires the researcher to fill all steps of a systematic review. There are some software packages specifically developed to conduct meta-analyses. R is a very resourceful open source package, but its use in health is still limited, due mostly to the need of programming instead of a point-and-click interface. Additionally, the first three programs do not have free access, with prices ranging from $250 to over $30,000 depending on version and country. These can be downloaded, but are not always easy for the researcher to understand or customize. General purpose statistical packages such as SPSS, Stata, SAS, and R can be used to perform meta-analyses, but it is not their primary function and hence they all require external macros or coding. Some of the studies are not concerned with the assessment of relative risks or odds ratios, but are focused on a summary statistics of incidence or prevalence. Meta-analyses of these studies are becoming more common, particularly after publication of the MOOSE statement. Although reviews of interventional studies, especially clinical trials, provide the best evidence, there are several situations in which observational studies are the only alternative. Performing a search on Pubmed limiting to the type of article, the Mesh term "meta-analysis" will wield 4223 results in 2010 only. Meta-analyses and systematic reviews are necessary to synthesize the ever-growing data obtained from primary research.
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