TITLE PAGE

Title: ???

Authors:??? 1, ??? 2

Affiliations:

1 ???

2 ???

Corresponding authors:

Name: ??

Address:??

Telephone:+66-xx-xxx xxxx

Fax:+66-xx-xxx xxxx

e-Mail:??@??.??

Type of contribution:xx

Running title:xx

Number of words in the abstract:xxx

Number of words in the text:x,xxx

Number of tables:x

Number of figures:x

1

TITLE OF THE STUDY

Lists of authors' name, highest degree of education, and name of institution

ABSTRACT

Background: ???

Objective: ???

Design: ???

Setting: ???

Main outcome measures: ???

Results: ???

Conclusions: ???

INTRODUCTION

(Example 1 of important phrases : ". . . is a common problem worldwide. Estimates of prevalence vary from . . . to . . . Reports have shown an association between . . . and . . . A recentprospective cohort study followed pregnant women with . . . showed that . . . Additionally, a recentreview of . . suggested . . . It thus seems plausible to speculate that . . . may be associated with an increased risk of . . . However, little is known about the long term outcome of . . . No study hasyet reported in . . . Most studies have been cross sectional, often utilisingpopulations of participants in clinical settings. Other prospectivestudies do not extend beyond . . . We aimed to elucidatethe associations between . . . and . . . factorsin a sample of the general population and to determine whether. . . in . . . is associated with an increased risk of. . . in infant.")

(Example 2 of important phrases : "In recent years, there has been an increased awareness of the potential impact of ???. Moreover, the traditional methods for treating ??? are expensive and can have inadequate facilities (1). This is particularly true in developing countries. This has led to the use of alternative intervention. The use of ??? is one such intervention which has received considerable attention (2)".)

Background: What is the context of this problem? What is the current management for this problem?

Problem Statement: What is already known on this topic? What is it we don’t know or still controversy? What is the gap in our knowledge this research will fill? What needs to be improved?

Rationale: Why is this research important? Who will benefit? Why do we need to know this? Why does this situation, method, model or piece of equipment need to be improved?

Objectives: What steps had been taken to try and fill this gap or improve the situation?

What will this study add? So what?

METHODS

Design of the study:

Outcome measurements:

Potential confounders:

Statistical analyses

Sample size calculation was based on the main statistical methods that used to estimate the magnitude of effect. Thus the sample size for logistic regression was used. The calculation was based on methods proposed by Hsieh (1991).

From the entire cohort we excluded from analysis . . . individuals (?%) with missing data on . . . Thosewith missing data on . . . (?%) were included.

We considered the outcome could be more similar within than between the study sites and affected by a number of potential confounding factors. Thus we analyzed the data using logistic regression implemented under generalized estimating equations (GEEs) framework. We initially explored (bivariate analysis) the relation between . . . and the other variables including . . ., expressed both as percentages and as odds ratioswith 95% confidence intervals.

The initial model contained all variables that were known to be bio-sociologically important and those with p-value of bivariate analysis was 0.2 or less. Interaction terms that were clinically meaningful and p-value of 0.2 or less were also included. Backward elimination were used as methods for variable selection following methods proposed by Kleinbaum (1996). We then obtained fully adjusted odds ratios and 95% confidence intervals.

Model adequacy assessments were performed by examining for goodness of fit and most influential observation. Sensitivity analysis was also performed for the appearance of influential observations and missing values.

We regarded a two sided p-value less than 0.05 or a 95% confidence interval excluding thevalue 1.0 for the rate ratio or 0 for the rate difference assignificant. All analyses were undertaken using STATA version6 (StataCorp, College Station,TX).

RESULTS

Characteristics of the study subjects

Main findings

DISCUSSION

Explain the findings: Comments on whether or not the results were expected, and presents explanations for the results, particularly for those that are unexpected or unsatisfactory.

Reference to previous researches: Compare the results with those reported in the literature, or use of the literature to support a claim, hypothesis or deduction (Deduction refers to a claim for how the results can be applied more generally. That is, a conclusion based on reasoning from the results, e.g. we fed fish a new feed, all the fish gained weight, therefore the new feed causes fish to gain weight. Hypothesis refers to a more general claim or possible conclusion arising from the results (i.e., which will be proved or disproved in later research.).

Strength of the study:

Limitations of the study:

  • Can selection bias distort the findings?
  • Can information bias distort the findings?
  • Can confounding bias distort the findings?

Conclusions: What was learnt (i.e., answers to the research questions)? What remains to be learnt (i.e., generate new research question for future research)? The shortcomings of what was done. The benefits, advantages, applications, etc. of the findings. Recommendations.

ACKNOWLEDGEMENTS

Contributors: All authors were actively involved in the planning and design of the study. AA collated and analysed the data and was the principal writer of the paper. BB helped in interpretation of the data and writing of the paper. CC took part in the study design. DD undertook all statistical analyses and wrote the original draft of the paper. AA, BB, and CC are contributed to the final version of the paper and act as guarantors.

REFERENCES

  1. Hsieh FY, Bloch DA, Larsen MD: A simple method of sample size calculation for linear and logistic regression. Statistics in medicine 1998, 17(14):1623-1634.