Meta-Analysis Services - statswork

Meta-Analysis Services

Your search for precise and standardised Meta-Analysis Services ends here! Witness the capability of holistic research with our visionary experts.

Meta-Analysis Services

Your search for precise and standardised Meta-Analysis Services ends here! Witness the capability of holistic research with our visionary experts.

Our Capabilities

A single study can provide insights into a problem that may be accurate, but what if more than two studies on the same problem gave contradicting results? What do you think is the right outcome and how do you make the right decision? Well, to eliminate such inaccuracies, Statswork’s meta-analysis services offer a solution. Through our critical statistical methods, we eliminate selection bias errors and other inconsistencies.
We have an integrated way to determine the accuracy of your research findings through our refined methods of meta-analysis. By aggregating data from various studies, we uplift statistical power to provide accurate research findings that remove all the inconsistencies. With our highly intellectual statisticians and data researchers, we help you to make clear and accurate decisions that are supported by our empirical reports.

Data Extraction Services

Based on specific inclusion and exclusion criterions, we extract data from various sources such as EMBASE, MEDLINE, and Cochrane using skillful data extraction methods, which is later analysed. We obtain a diverse range of systematic reviews required for thorough analysis. Our data extraction service goes through a broad and critical process to present a reliable and validated dataset.

The Key Aspects Involve

Source Identification: Identifying the right sources for data, which are required for the study.
Data Retrieval: Extracting relevant data from the identified sources using top-tier techniques and tools.
Data Cleaning: Transforming the raw data into a standardised format by removing inconsistencies and fixing errors.
Integration: Merging the extracted dataset with existing databases for comprehensive analysis.
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Systematic Reviews

Researchers at Statswork derive unbiased results ensuring the validity of medical interventions and practices. Along with data scientists, we have medical research professionals who handle the thematic side of the study. We methodically review existing research on a particular topic for a clear insight, which forms the basis for meta-analysis.

  • – Our research question contains inclusion and exclusion criteria that adhere to the PICOS framework.
  • – Through our critical systematic review, we minimise the bias in selecting and analysing studies.

Meta-Analysis

We critically observe multiple intervention methods and come up with an objective conclusion based on them. Our advanced visual representations communicate the relationships and patterns from various studies. We perform network meta-analysis, dichotomous comparison, meta-regression, sensitivity analysis, and assessment of heterogeneity, as well as prevalence and incidence synthesis.

For clinical studies and medical research, we offer a detailed report that adheres to the standards of PRISMA with a clear presentation with a detailed visualisation of findings.

The Key Aspects Involve

Forest Plot: Our forest plot interpretation provides summarised results of various studies involved in meta-analysis. 

Funnel Plot: Our funnel plot helps you to identify the possible biases in the study results through a straightforward visualisation.

Sensitivity: Our sensitivity charts allow you to assess the effectiveness of diagnostic tools and other methods through concise visuals. 

Specificity: Our specificity reports determine the accuracy of the diagnostic tests that reduce false positives in a simple manner. 

Bubble plot: Our bubble plot visualisations help you to comprehend the relationships between more than two variables in complex domains.

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Check Out Our Sample Works of Meta Analysis

Stastwork has been offering outstanding meta-analysis help for more than a decade. Our expertise in data handling and research methodology ensures that we consistently deliver the best results. We also excel in systematic review services that go hand in hand with our meta-analysis services. Hence, we possess a broad knowledge of research analysis that delivers a comprehensive output.

Integrated Care for Concurrent Disorders

Integrated Care for Concurrent Disorders

The main objective of this study was to determine whether or not the existing service health models were effective in treating concurrent disorders and, if effective, how they reduce the high rates of patients with this disorder. Various databases were used to investigate the effectiveness of service delivery models in treating mental health and substance use disorders. Experimental studies that were conducted on patients with substance misuse coupled with a serious mental illness were considered.
Methylene Blue for Sentinel Node Detection.

Methylene Blue for Sentinel Node Detection.

In order to examine breast cancer in patients for local metastasis, sentinel node mapping has been thought as the favourable method. This method is on the basis of the path that a cancer cell takes from the primary breast tumour for metastasis to the local lymph node. The first receiver of the metastatic disease is this lymph node, and if this is negative, it can be assumed that the tumour does not involve all other lymph nodes in that region are not involved by the tumour.
Fingerprint Patterns in Celiac, Alzheimer’s, and Down Syndrome

Fingerprint Patterns in Celiac, Alzheimer’s, and Down Syndrome

We conducted a search on MEDLINE and other databases for prospective studies related to celiac disease, Alzheimer’s disease, and Down syndrome. From a total of 14 studies we identified, we included two studies on celiac disease, four studies on Alzheimer’s disease, and two studies on Down syndrome. In analysis, we looked at specific fingerprint patterns: whorls (more than 4) and ulnar loops (fewer than 4). In our meta-analysis, we summarised the findings using measures of sensitivity, specificity, and accuracy.

A Transparent Chart of Our Workflow

Statswork’s Department of Data Science and Statistics collaborate with subject matter experts to harmoniously derive qualified results. Our team of experts critically studies the problem to deeply understand the research question.

meta analysis work flow
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Journal Formatting Services

Define your research question

We work with you to develop a clear research question that is targeted to your individual goals and demands.

Design collection plan

Conducting a thorough literature search

To locate relevant studies, we conduct thorough searches across numerous databases using relevant keywords and predefined parameters.

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Screening and selecting studies

We carefully examine titles, abstracts, and complete texts to pick articles that fulfil our inclusion criteria for analysis.

Journal Formatting Services

Data Extraction

We extract critical data from selected research, such as sample sizes, outcomes, and impact sizes, while assuring correctness and consistency.

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Journal Formatting Services

Assessing Research Quality

We use proven methods to evaluate the technical quality of the studies included and also the reliability and validity of their results.

Journal Formatting Services

Analysing Data

We estimate effect sizes and perform statistical assessments employing fixed or random effects models depending on the characteristics of the data.

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Interpreting the Results

We summarise data, evaluate clinical relevance, and discuss implications for practice in accordance with your study objectives.

Journal Formatting Services

Reporting Findings

We create a complete report in accordance with PRISMA principles, which includes methodologies, results, limits, and recommendations tailored to your specific needs.

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Our Service Features
Our Clients
DAI
voltas
policy navigationgroup
pennarindustries
winngroup
i3development
uhn
kenya
chenmed
university
canons
Why Choose Statswork as your Meta-Analysis Service Provider?
Statswork considers you as a valuable partner rather than a client. We work attentively on your goals to make you achieve and go far beyond that. Our work ethic strictly emphasises your privacy, satisfaction and fairness.
Technology Development

Innovative Data Solutions

We don’t just traditionally analyse them. Instead, our approach contains strategised solutions that are embedded within the service.

Customised strategy

Shortest turnaround time

We are perfectionists in terms of punctuality. We ensure your project is delivered on the promised date, if not early.

Subject matter wisdom

Multiple levels of quality assurance

Our process includes multiple levels of quality check that ensures standards are maintained in all dimensions to present a detailed output.

24/7 personalised support

24/7 support and care

Statswork backs you with 24-hour support, offering complete technical assistance and guidance 24/7.

Proficiency in field

Transparency in our workflow

Our processes are open, clients are allowed to be involved in every step, keeping them abreast of the happenings behind the scenes.

Secured environment

Rigid security measures

Our security protocols serve as a fortification of data, which prioritises your privacy over anything else.

Our Customers Experience

Statswork was my first choice for statistical help, I got my project back before the due date and took stress off my plate. I am too thankful to have found Statswork.
David John
Stats work restored my hope in research. Their meta-analysis helped us refine our clinical trial methods and resulted in accuracy, which got me my second doctorate.
Alice
What they left me with, was nothing sort of ordinary. Their accuracy and detail in the results overwhelmed me. I thank and will always recommend Statswork for anyone who needs it.
Michael Johnson

Frequently Asked Questions

Meta-analysis is one of the statistical methods which consolidates and provides a filtered outcome by analysing multiple studies on a single research problem.
Define your research problems clearly before collecting relevant data and literature. Select a statistical method and perform a meta-analysis of the collected data. Now, interpret the outcomes of the analysis.
In research, meta-analysis refers to the process of aggregating varying interpretations of multiple studies to summarise them. It is used to validate the accuracy of research findings on a single problem.
At statswork, we work in a team that has a great suite of experts with various specialisations to ensure a holistic contribution to your needs.
Systematic reviews collect and evaluate relevant studies, whereas meta-analysis statistically combines them to provide a quantitative summary.
Meta-analysis is one of the statistical methods which consolidates and provides a filtered outcome by analysing multiple studies on a single research problem.
Define your research problems clearly before collecting relevant data and literature. Select a statistical method and perform a meta-analysis of the collected data. Now, interpret the outcomes of the analysis.
In research, meta-analysis refers to the process of aggregating varying interpretations of multiple studies to summarise them. It is used to validate the accuracy of research findings on a single problem.
At statswork, we work in a team that has a great suite of experts with various specialisations to ensure a holistic contribution to your needs.
Systematic reviews collect and evaluate relevant studies, whereas meta-analysis statistically combines them to provide a quantitative summary.
Some of the common methods of meta-analysis include fixed effect, random effect and sensitivity analysis.
A forest plot is a visual representation of the findings that are found in meta-analysis. It visually demonstrates the overall effect size.
For meta-analysis, software like RevMan, R, CMA and Stata are primarily used.
Systematic reviews often form a strong foundation for meta-analysis by containing collective studies and their assessment comprehensively.
  1. Define the research question and develop a protocol.
  2. Search for relevant literature and studies from databases.
  3. Extract the data and conduct a thorough analysis.
The common challenges in meta-analysis arise from publication bias, methodological variations and differing outcome measures.
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