자세한 기능 목록

스프레드시트 인터페이스로 작업
처리 효과(또는 효과 크기)를 자동으로 계산
메타 분석을 빠르고 정확하게 수행
한 번의 클릭으로 고해상도 삼림 플롯 만들기
보고서
비디오 자습서
예측 구간
일반적인 실수와이를 피하는 방법
누적 메타 분석을 사용하여 시간이 지남에 따라 증거가 어떻게 변했는지 확인
"Remove-One" 분석을 사용하여 각 연구의 영향을 측정합니다.
데이터의 하위 집합 작업
연구 내에서 여러 하위 그룹 또는 결과로 작업
중재자 변수의 영향 평가
출판 편향의 잠재적 영향 평가

스프레드시트 인터페이스로 작업

데이터를 직접 입력하거나 다른 프로그램에서 데이터 가져 오기

You can type data directly into the spreadsheet, much as you would with any spreadsheet-based program. Or, if you are currently using another program for meta-analysis, you can either copy data directly from that program or import it using a Wizard.

연구 내에 여러 하위 그룹 또는 결과가 있는 경우 어떻게 합니까?

The program allows you to work with studies that report data for more than one subgroup, outcome, time-point, or comparison. The program makes it easy to enter data for these studies, and offers a number of options for working with them in the analysis.

처리 효과(또는 효과 크기)를 자동으로 계산

In every meta-analysis you start with the published summary data for each study and compute the treatment effect (or effect size). For example, if a study reports the number of events in each group you might compute the odds ratio. Or, if a study reports means and standard deviations you might compute the standardized mean difference. This process of computing effect sizes is typically tedious and time consuming. In some cases, especially when studies present data in different formats, the process is also difficult and prone to error.

CMA를 사용하면 프로세스가 빠르고 정확합니다.

With CMA you enter whatever summary data was reported in the published study, and the program computes the effect size from that summary data. For example, you could enter events and sample size, and the program would compute the odds ratio. Or, you could enter means and standard deviations, and the program would compute the standardized mean difference. Three examples (selected from more than a hundred options) are shown here.



내 데이터가 다른 형식인 경우 어떻게 해야 합니까?

What if your studies reported data in some other format? Perhaps you have studies that reported only a p-value and sample size. Or, you have studies that reported an odds ratio and confidence limits. With any other program you would need to compute the effect size and variance for each study before proceeding to the analysis. By contrast, CMA allows you to enter almost any kind of data – it includes 100 formats for data entry similar to the three shown above. Simply locate your data type in a list and CMA will create the corresponding columns in the spreadsheet.

> 전체 목록을 보려면 여기를 클릭하십시오.

프로그램은 이러한 효과를 계산하기 위해 어떤 공식을 사용합니까?

To see the formula used to compute an effect size, double-click on that effect size. The program opens a dialog box that shows the exact formula used and also all details of the computation for that specific row.

치료 효과의 다른 지수를 사용하려면 어떻게해야합니까?

In one of the examples shown above we entered events and sample size and the program computed the odds ratio and risk ratio. What if you would prefer to work with the risk ratio? Or what if you wanted to compute the standardized mean difference corresponding to the odds ratio? In another example we entered means and standard deviations and the program computed the standardized mean difference. What if you would prefer to work with the raw mean difference, or to compute the correlation corresponding to the standardized mean difference?

CMA를 사용하면 선택한 인덱스로 작업하고 인덱스 간에 앞뒤로 전환할 수 있습니다.

예를 들어, 사건과 표본 크기를 입력한 경우 프로그램은 승산비, 로그 승산비, 위험 비율, 로그 위험 비율, 위험 차이, 표준화 평균 차이(d), 편향 수정 표준화 평균 차이(g), 상관 관계 및 Fisher's z를 계산합니다. 또는 평균과 표준 편차를 입력하면 원시 평균 차이, 표준화 평균 차이(d), 편향 수정 표준화 평균 차이(g), 상관 관계, Fisher의 z, 로그 승산비 및 승산비가 계산됩니다.

이러한 예제는 지원되는 형식 및 인덱스의 하위 집합입니다.

다른 연구에서 다른 종류의 데이터를보고하면 어떻게됩니까?

Above, we showed that you can customize the data entry screen to accept almost any kind of data. But what different studies provide different kinds of data? For example, what if one study reported events and sample size while another reported the odds ratio and confidence interval? How would you get both kinds of data into the program?

CMA allows you to mix and match the different data formats. You can enter events and sample size for the first few studies, then odds ratio and confidence interval for the next few studies, log odds ratios with variances for others, and so on. Or, you can enter means and standard deviations for some studies, p-values for other studies, t-values for others, and so on. You can customize the spreadsheet with as many kinds of data formats as you like. The program will compute the effect size from each of them and (to the extent possible) allow you to include them all in the same analysis. CMA is the only program to offer this feature.

내 연구의 일부(또는 전체)에 사전 포스트 또는 크로스오버 디자인이 포함된 경우 어떻게 합니까?

CMA에는 20개 이상의 사전 포스트 또는 크로스오버 설계를 위한 템플릿이 포함되어 있으며, 이는 표준 오류를 달리 계산하기 어려울 수 있기 때문에 특히 중요합니다. 또한 이러한 연구를 사후 테스트만 사용한 연구와 혼합하고 일치시킬 수 있습니다.

> For a list of all formats click here.

효과 크기를 이미 계산한 경우 어떻게 해야 합니까?

효과 크기와 분산(또는 표준 오차)을 이미 계산한 경우 직접 입력할 수 있습니다(다른 형식으로 데이터를 입력하는 것과 동일).


이진, 연속 및 상관 데이터를 혼합할 수 있습니까?

As explained above, the program allows you to enter summary data in more than one format – for example, events and sample size for one study and odds ratios with confidence intervals for another. But in this example both studies used binary data. What if some studies report binary data (events and sample size) while others report continuous data (means and standard deviations) or correlational data?

The program is able to convert across these different classes of data. It will convert among odds ratios, standardized mean difference, and correlations so that all may be used in the same analysis.

효과 크기나 치료 효과가 아닌 점 추정치를 보는 연구가 있는 경우 어떻게 합니까?

While most meta-analyses work with effect sizes (which assess the relationship between two variables) some are used to estimate a risk, rate, or mean in one group (for example, “What is the risk of Lyme disease?”). CMA will work with these effects (or point estimates) as well.


회귀 가중치에 대한 메타 분석을 실행할 수 있습니까?

Yes. In addition to being able to work with recognized effects (such as odds ratios and mean differences) the program is able to work with generic point estimates which may be analyzed either in their original scale or on a log scale.

메타 분석을 빠르고 정확하게 수행

한 번의 클릭으로 핵심 메타 분석을 실행하고 다음 모든 항목에 대한 로드맵 역할을 하는 디스플레이를 생성합니다.

This display is an interactive forest plot that yields a clear sense of the data - How many studies are included in the analysis, how precise is each of the studies, whether the effect is consistent from study to study or varies substantially across studies, and so on. You can then customize this display as needed. Add or remove columns, set computational options, open tables with additional statistics. Some examples follow.

연구 가중치 표시

한 번의 클릭으로 각 스터디에 할당된 상대적 가중치를 보여주는 열을 포함할 수 있습니다. 이 메커니즘을 사용하면 결합 된 효과가 많은 연구의 기능인지 또는 주로 연구의 작은 하위 집합에 의해 주도되었는지 명확 해집니다.

계산 모델 선택

Click on a tab to select the fixed effect model or the random effects model. You can also display the two simultaneously, which makes it possible to see how the point estimate and confidence interval differ between the two models.

계산 모델이 연구 가중치에 미치는 영향 이해

The program will also display the relative weights for a fixed effect analysis and a random effects analysis side-by-side. This helps to explain why the combined effect shifts as we move from fixed effect to a random effects model (See paper).

분석 화면 사용자 지정

You have full control over the statistics displayed for each study. You can display basic statistics such as the effect size, standard error, and confidence limits. You can display counts, such as events and sample size for each group. You can display diagnostics for each study, such as the residual (the distance from the study to the combined effect).

효과 크기의 인덱스 선택

The tool bar includes a drop-down box that lists all available indices for the treatment effect (or effect size). When you select an effect size such as the odds ratio or standardized mean difference, all statistics, weights, and graphs, are updated automatically.

계산의 모든 세부 정보 표시

All computations are displayed on a spreadsheet. You can view this spreadsheet and actually follow all details of the computation. If you are using your own spreadsheet for meta-analysis you can compare this spreadsheet with your own. This also serves as a unique teaching tool.

한 번의 클릭으로 고해상도 삼림 플롯 만들기

A key element in any meta-analysis is the forest plot – a plot that shows the effect size and precision for each study as well as the combined effect. This plot puts a face on the analysis – it shows whether the combined effect is based on a few studies or many, whether the effect size is consistent or varies, and so on. As such, the forest plot plays a central role in helping the researcher to understand the data, and also to convey the findings to others.

Most other meta-analysis programs use graphics engines that were developed for other purposes and push them into service for creating forest plots. By contrast, the plotting engine in CMA was developed specifically for the purpose of meta-analysis. It is very easy to use and provides a wide range of important options.

Create a high-resolution plot in one click and then customize any element on the plot. Select a symbol for studies, for subgroups, and for overall effect. Optionally, specify that symbols should be proportional in size to study weights, so the studies that contribute the most to the combined effect are easy to spot. Set colors and fonts for each element on the graph, and then export to Word™ or PowerPoint™ in a single click!

> Word™에서 보려면 여기를 클릭하십시오.

파워포인트™로 플롯 내보내기

With one click you can open PowerPoint™ and insert a copy of the current slide. The whole process takes about 2 seconds.

> 파워포인트™에서 보려면 여기를 클릭하세요

보고서

한 번의 클릭으로 프로그램은 모든 통계를 게시하기에 적합한 형식으로 보고하는 문서를 생성합니다.

두 번째 클릭으로 프로그램은이 문서에 주석을 달고 모든 통계의 의미와 가정 및 제한 사항을 설명합니다.

세 번째 클릭으로 프로그램은이 문서를 Word로 내 보냅니다.

샘플 보고서를 보려면 여기를 클릭하십시오.

비디오 자습서

We have developed videos of case studies that show how to run an analysis from start to finish. This includes how to enter data, how to run the analysis, how to create plots, how to compare the effect size in different subgroups, and so on.

Critically, each section of the video explains now only how to perform specific functions, but what purpose these functions serve in the context of the analysis, and how to understand the meaning of the statistics.

Each case study runs about ninety minutes. You can watch one from start to finish to learn how to perform a meta-analysis and report it properly. Or, from any screen in the program you can jump to the part of the video that explains all functions on that screen.

예측 구간

In any meta-analysis it is important to report the mean effect size and also how widely the effect size varies across studies. This dispersion is addressed by the prediction interval. This allows us to report, for example, that the mean effect size is a standardized mean difference of 0.50 but that in any single population the true effect size could be as low as 0.05 or as high as 0.95. Many guidelines for reporting a meta-analysis now request the inclusion of prediction intervals.

In Version 4 the program offers the option to display the prediction interval as part of the forest plot. Additionally, with one click you can create a plot that shows the entire distribution of true effects. With one more click you can export this to Word or PowerPoint.

일반적인 실수와이를 피하는 방법

우리는 최근에 메타 분석의 일반적인 실수와 그것을 피하는 방법이라는 책을 출판했습니다.

이 책에는 통계 모델 선택, 이질성과 관련된 통계, 연구의 하위 그룹 비교, 출판 편향 등과 같은 영역의 실수가 포함되어 있습니다.

프로그램의 모든 화면에서 책의 관련 섹션이있는 PDF를 여는 링크를 클릭 할 수 있습니다.

누적 메타 분석을 사용하여 시간이 지남에 따라 증거가 어떻게 변했는지 확인

A cumulative meta-analysis is actually a series of meta-analyses, where each analysis in the sequence incorporates one additional study. For example, the first row in the analysis might include a study published in 1990, the next row would include studies published in 1990 and 1991, and so on. A cumulative meta-analysis may be done retrospectively, to show how the body of evidence has shifted over time (see the Lau study, for example), or prospectively, with new studies being added to the body of evidence as they are completed (see the Childbirth example).

While cumulative meta-analysis is most often used to track evidence over time, it can also be used to show how the evidence shifts as a function of other factors. For example, we could sort the data by study size and run a cumulative analysis. In this case the program would show the combined effect with only the largest studies included (toward the top) and how this effect shifted as smaller studies were added to the analysis (see the passive smoking example). Similarly, we could start with the higher quality studies and see how the effect shifts as other studies are added.

"Remove-One" 분석을 사용하여 각 연구의 영향을 측정합니다.

As part of a sensitivity analysis we might want to assess the impact of each study on the combined effect. For example, what was the impact on the combined effect of an outlier or of an especially large study? Or, did a small study have any impact at all?

To address these kinds of questions the program will automatically run the analysis with all studies except the first, then all studies except the second, and so on. The resulting plot shows the impact of each study at a glance.

또한 스터디 또는 스터디 세트를 제거한 상태에서 분석을 실행할 수 있으며, 이름 또는 중재자 변수 값으로 선택할 수 있습니다.

데이터의 하위 집합 작업

When running the analysis you can select by (or filter by) any variable or combinations of variables. You could include or exclude studies by study name. You could include studies that had been rated “Yes” for “Double-blind”. You could include studies where the age had been coded as “Elderly” and the patient type as “Chronic.

연구 내에서 여러 하위 그룹 또는 결과로 작업

이 프로그램을 사용하면 둘 이상의 하위 그룹, 결과, 시점 또는 연구 내 비교에 대한 데이터를 입력 할 수 있으며 분석에서이를 처리하기위한 다양한 옵션을 제공합니다.

중재자 변수의 영향 평가

효과 크기가 연구마다 크게 다를 때 메타 분석의 중요한 목표는 이러한 변동의 이유를 이해하는 것입니다.

Use analysis of variance to assess the impact of categorical moderators. For example, “Is the treatment more effective for acute patients than for chronic patients?” or “Is homework a more effective intervention than tutoring?”

Use meta-regression to assess the impact of continuous moderator variables. For example, “Does the treatment effect increase as a function of dosage?”, or “Is the magnitude of the effect size related to the age of the students?”

출판 편향의 잠재적 영향 평가

Meta-analysis provides a mathematically accurate synthesis of available data, but there may be concern that significant studies were more likely to be published than non-significant studies, and therefore the pool of available data may be biased. The program includes a set of functions that can be used to assess the potential impact of this bias, as a kind of sensitivity analysis.

일하는 사람들
포괄적인 메타 분석

10일 체험판 다운로드


"Comprehensive Meta‐Analysis software is like a magic wand. The simple and clear interface (like an Excel sheet) will guide you to do complicated meta‐analysis within only a few clicks. The comprehensive formats included in the software allow researchers to input the data in various ways. It provides clear outputs and high‐resolution graphs which can be imported to Microsoft Word. I especially love the feature that shows you the calculation steps so you can check whether you’ve run it correctly. It also provides advanced sub‐group analysis, moderator analysis, meta‐regression, and publication‐bias analysis. This software is a lifesaver! Meta‐analysis becomes very easy with the help of Comprehensive Meta‐Analysis. I am sure I will use this software for upcoming meta‐analyses in the future."

Jih‐Hsuan Lin (Tammy), Ph.D. Candidate - Media and Information Studies Program, Department of Telecommunication, Information Studies and Media, Michigan State University, East Lansing, MI


"I absolutely loved this program. Without it, I don't know how I would have gotten this series of metaanalyses done, let alone published (see attached). Very easy to use, many great features, and lots of support from you all (i.e., the emails about updates, training opportunities, etc.)."

Robert A. Schug, Ph.D. - Assistant Professor of Criminal Justice and Forensic Psychology, Department of Criminal Justice, California State University, Long Beach


"As a behavioral scientist who is newly developing expertise in using meta‐analysis, I have found CMA to be an invaluable tool. It is user‐friendly, but avoids superficiality and provides me with all the necessary technical depth I need. I have found CMA to be an outstanding program."

제임스 맥킬롭


"CMA has been a huge asset in my research on motivation and self‐regulation. I have used this software to conduct multiple meta‐analyses, each requiring different and multiple formats of effect size. CMA surpassed my needs and expectations every time. The software is really "comprehensive" yet exceptionally user‐friendly. Fellows and students have learned to use it in just one sitting. I highly recommend CMA to any researcher wishing to conduct meta‐analysis in a highly effective and efficient manner."

Patrick Gaudreau, Ph.D. - Professeur agrégé/Associate Professor Université d'Ottawa/University of Ottawa École de Psychologie/School of Psychology Ottawa, ON, Canada


"I am an advanced graduate student in clinical psychology, and CMA software was integrated into a meta‐analysis course I recently took. I feel very fortunate to have been trained in meta‐analyses at a time when we have this software because CMA is easy and, I dare say, fun to use. Rather than spending countless hours computing my own effect sizes and creating syntax, the program did it for me, which allowed me to spend my time really looking at the data, both graphically and numerically. I bought CMA for myself and would recommend it to anyone looking to learn the art of meta‐analysis."

레이첼 허셴버그


"I am impressed with the ease or simplicity of the Comprehensive Meta‐Analysis, not only in data entry but also the data generated. Unlike some of the free software available for meta‐analysis, I found the Comprehensive Meta‐Analysis user‐friendly, generating clear graphs and effect sizes. I took a long time to work out some of the free software available by some of my colleagues and found them very userunfriendly, confusing, and the graphs generated not easy on the eye. After chancing on Comprehensive Meta‐Analysis during a Google search and having a go at it during the free trial, I was keen to get my hands on it and have recommended it to some of colleagues. It is definitely worth getting it as it makes meta‐analysis non‐daunting and non‐scary especially for students pursuing their Masters or PhDs."

리 와이 신디, NG


"CMA has been the vehicle to get me started with my PhD! A meta‐analysis is the optimal starting point, as it allows you to clearly see the state‐of‐the‐art in your field and pose new questions. CMA, with its self‐explanatory, user‐friendly platform is the kind of software you would hope to be using for your meta‐analyses! Now my students are starting off their journeys in research by performing a metaanalysis using CMA!"

Dr. Papadatou‐Pastou Marietta - Lecturer, University of Athens

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포괄적인 메타 분석

소프트웨어 이미지

종합 메타 분석(CMA)은 메타 분석을 위한 강력한 컴퓨터 프로그램입니다. 이 프로그램은 사용 편의성과 다양한 계산 옵션 및 정교한 그래픽을 결합합니다.