A research that was meticulously planned, conducted and analyzed may still face rejection by most international journals during editorial peer review due to poor language skills that makes the manuscript incomprehensible. Many journals, thus, require the manuscript to be proof read by persons with full proficiency in the English language and with a strong scientific background. Language review involves spelling and grammar correction, sentence restructuring, enhancing the readability and flow of ideas.
Student Package
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Literature review consultation
Sampling strategy
Study design selection
IRB forms assistance
Informed consent creation
Data cleaning
Data coding
Simple statistics
Data visualization
Healthcare Worker Package
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Sampling strategy
Study design selection
Research topic refinement
Data cleaning
Data coding
Complex statistics
Data visualization
Language review
Scientific review
Journal selection
Formatting
Reference validation
Scientific Review
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Owing to the journal’s long waiting time for peer review, it is a good idea to get your manuscript critically evaluated for any scientific and technical issues by a person with expertise on the research topic that can help you improve any potential gaps related to methodology, analysis, reporting, significance and generalizability of findings. Any issues related to clarity of the manuscript can be addressed. This will enable you to save time and have a comparatively smoother journal peer review.
Formatting
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Formatting entails an outward polishing of the manuscript and organizing it as per the instructions of the target journal. It includes adhering to the word limit, abstract structure, page layout, reference style, manuscript blinding for peer review, and table and figure design guidelines of the journal.
Data Cleaning
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Data cleanup is a way of preparing and fixing the collected data for analysis by removing or modifying data that is incorrect, duplicated, incomplete, irrelevant, or improperly formatted. This data is usually not important or helpful when it comes to analyzing data because it may corrupt the process or provide inaccurate results. Most importantly, the goal of data cleaning is to create data sets that are standardized and uniform to allow analytical processes to be done.
Data Coding
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The voluminous data obtained through research undergoes a process of data coding which involves summarizing and converting the data collected to a set of consistent categories. This enables the data to be understood by computer software’s and conduct analysis.
Simple Statistics
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Simple statistics provide descriptive information regarding the variables in the data set. It includes: Measures of Frequency (Count, Percent, Frequency), Measures of Central Tendency (Mean, Median, and Mode), Measures of Dispersion or Variation (Range, Variance, Standard Deviation), and Measures of Position (Percentile Ranks, Quartile Ranks).
Professor Package
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Data cleaning
Data coding
Complex statistics
Data visualization
Language review
Scientific review
Biostatistics review
Formatting
Submission
Journal selection
Reference validation
Complex Statistics Package
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Data cleaning
Data coding
Complex statistics
Data visualization
Research Topic Refinement
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We help you navigate through the process of selecting an appropriate research topic in your field of study and then guide you to generate research questions based on gaps identified in the literature.
Study Design Selection
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We walk you through the task of choosing the appropriate research study design from the many types of designs, each with its advantages and limitations used to collect and analyze data on variables specified in a particular research problem and deciding the most suitable methods and procedures to be used.
