Monte Carlo Investigations for Relative Efficiency of Stratified Random Sampling Scheme for Estimation of Relative Risk in Case-Control Studies

1993 ◽  
Vol 35 (6) ◽  
pp. 707-714
Author(s):  
Padam Singh ◽  
T. C. Gupta
Keyword(s):  
Monte Carlo ◽  
Relative Risk ◽  
Random Sampling ◽  
Relative Efficiency ◽  
Case Control ◽  
Sampling Scheme ◽  
Stratified Random Sampling ◽  
Case Control Studies

The results obtained from studies of causation

2017 ◽  
Author(s):  
Mark Elwood
Keyword(s):  
Relative Risk ◽  
Intervention Studies ◽  
Case Control ◽  
Risk Difference ◽  
Attributable Risk ◽  
Number Needed To Treat ◽  
Case Control Studies ◽  
Sampling Schemes ◽  
Multiplicative Models ◽  
The Relationship

This chapter shows the format and derivation of results from studies. Cohort and intervention studies yield relative risk and risk difference, also known as attributable risk, and number needed to treat (NNT). Count and person-time methods are shown. Additive and multiplicative models for two or more exposures are shown. Case-control studies give primarily odds ratio; the relationship between this and relative risk is explained. Different sampling schemes for case-control studies include methods were a case can also be a control. Surveys yield results similar to cohort studies.

A Computer Program to Estimate Power and Relative Efficiency of Flexibly Matched Case-control Studies

2005 ◽  
Vol 44 (05) ◽  
pp. 693-696 ◽  
Author(s):  
O. Gefeller ◽  
H. Brenner ◽  
T. Stürmer
Keyword(s):  
Computer Program ◽  
Relative Efficiency ◽  
Odds Ratio ◽  
Null Hypothesis ◽  
Case Control ◽  
Case Control Studies ◽  
Test Statistic ◽  
Matched Case ◽  
Haenszel Test ◽  
Flexible Matching

Summary Objectives: We recently introduced the concept of flexible matching strategies with varying proportions of a dichotomous matching factor among controls to increase power and efficiency of case-control studies. We now present a method and a computer program to calculate power and relative efficiency compared to an unmatched design varying the proportion of the matching factor in controls over all possible values from 0 to 100 percent. Methods: For all these values, the program calculates the expected variance of the combined Mantel-Haenszel odds ratio and determines the power using the standard error of the expected combined Mantel-Haenszel odds ratio under the null hypothesis as derived from the Mantel-Haenszel test statistic without continuity correction. Results: Thereby, the program allows estimating the optimal prevalence of the matching factor in selected controls for a given scenario which often differs from the prevalence in cases. It furthermore allows to estimate loss in power and efficiency compared to optimal matching by suboptimal matching. Conclusions: Estimations like these are helpful with respect to the decision when to stop efforts to optimize the degree of matching during the recruitment of controls. Our program will strongly facilitate assessing the benefits of flexible matching strategies.

scholarly journals Association between green tea intake and risk of gastric cancer: a systematic review and dose–response meta-analysis of observational studies

2017 ◽  
Vol 20 (17) ◽  
pp. 3183-3192 ◽  
Author(s):  
Yanhong Huang ◽  
Hongru Chen ◽  
Liang Zhou ◽  
Gaoming Li ◽  
Dali Yi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Systematic Review ◽  
High Temperature ◽  
Relative Risk ◽  
Green Tea ◽  
Dose Response ◽  
Observational Studies ◽  
Meta Analysis ◽  
Case Control ◽  
Case Control Studies

AbstractObjectiveTo examine and quantify the potential dose–response relationship between green tea intake and the risk of gastric cancer.DesignWe searched PubMed, EMBASE, Web of Science, CBM, CNKI and VIP up to December 2015 without language restrictions.SettingA systematic review and dose–response meta-analysis of observational studies.SubjectsFive cohort studies and eight case–control studies.ResultsCompared with the lowest level of green tea intake, the pooled relative risk (95 % CI) of gastric cancer was 1·05 (0·90, 1·21, I2=20·3 %) for the cohort studies and the pooled OR (95 % CI) was 0·84 (0·74, 0·95, I2=48·3 %) for the case–control studies. The pooled relative risk of gastric cancer was 0·79 (0·63, 0·97, I2=63·8 %) for intake of 6 cups green tea/d, 0·59 (0·42, 0·82, I2=1·0 %) for 25 years of green tea intake and 7·60 (1·67, 34·60, I2=86·5 %) for drinking very hot green tea.ConclusionsDrinking green tea has a certain preventive effect on reducing the risk of gastric cancer, particularly for long-term and high-dose consumption. Drinking too high-temperature green tea may increase the risk of gastric cancer, but it is still unclear whether high-temperature green tea is a risk factor for gastric cancer. Further studies should be performed to obtain more detailed results, including other gastric cancer risk factors such as smoking and alcohol consumption and the dose of the effective components in green tea, to provide more reliable evidence-based medical references for the relationship between green tea and gastric cancer.

Validity in estimating relative risk in case-control studies

1973 ◽  
Vol 26 (4) ◽  
pp. 219-225 ◽  
Author(s):  
Daniel G. Seigel ◽  
Samuel W. Greenhouse
Keyword(s):  
Relative Risk ◽  
Case Control ◽  
Case Control Studies

scholarly journals Hubungan Antara Stimulasi Alat Permainan Edukatif Dengan Perkembangan Motorik Kasar Dan Halus Anak Usia Pre School Di Sekolah TK Kabupaten Tegal

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Feti Ariskha ◽  
Arista Adityasari Putri ◽  
Dwi Indah Iswanti
Keyword(s):  
Motor Development ◽  
Random Sampling ◽  
Case Control ◽  
School Age Children ◽  
Fine Motor ◽  
P Value ◽  
Stratified Random Sampling ◽  
School Age ◽  
Educational Tool ◽  
Chi Square

Kondisi Indonesia akhir tahun 2013, anak usia 4-6 tahun yang belum terlayani pendidikannya ada 13,0 juta (63,46%)  dari  17,6  juta.  Hasil  penelitian  /  kajian  yang  dilakukan  oleh  pusat  kurikulum,  balitbangnas menunjukkan bahwa hamper seluruh aspek perkembangan anak yang masuk Taman Kanak-Kanak mempunyai kemampuan yang lebih tinggi dari pada anak yang tidak masuk Taman Kanak-Kanak di kelas 1 Sekolah Dasar. Tujuan  penelitian  ini  untuk  mengetahui  hubungan  antara  Alat  Permainan  Edukatif  dengan  perkembangan motorik kasar dan halus anak usia pre school di sekolah TK Kabupaten Tegal. Penelitian ini menggunakan kuantitatif, desain case control dengan pendekatan restrospective. Populasi responden sebanyak 130 responden dengan teknik proportionate stratified random sampling, jumlah sampel sebanyak 30 responden. Data yang diperoleh dianalisis secara univariat dan bivariat menggunakan uji chi square. Hasil menunjukkan stimulasi Alat Permainan Edukatif dengan perkembangan motorik halus p-value fisher exact = 0,026 < 0,05 dan stimulasi Alat Permainan Edukatif dengan perkembangan motorik kasar  p-value fisher exact = 0, 002 < 0,05. Ada hubungan antara stimulasi Alat Permainan Edukatif dengan perkembangan motorik halus dan kasar anak usia pre school. Kata Kunci : Alat Permainan Edukatif, Perkembangan, Motorik Kasar, Motorik Halus, Anak usia pre school RELATIONSHIP BETWEEN EDUCATIONAL GAME STIMULATING WITH GROUND AND FINE MOTOR DEVELOPMENT OF PRE SCHOOL AGE CHILDREN IN TK SCHOOL, TEGAL REGENCY ABSTRACT Indonesia condition late 2013, children aged 4-6 years who have not served their education there are 13.0 million (63,46%) from 17.6 million. Results of research / studies carried out by the central curriculum, balitbangnas shows that almost all aspect of child development that enter Kindergarten has a higher ability than children who do not attend kindergarten in grade 1 primary school.  To determine the relationship between Games Educational tool with gross and fine motor development of pre-school age children in kindergarten Tegal. This study uses a quantitative, case control design with a retrospective approach. The population of respondents as many as 130 respondens with proportionate stratified random sampling, sample size of 30 respondents. Data were analyzed using univariate and bivariate using chi square test. Result showed stimulation games educational tool with fine motor development fisher exact p-value = 0.026<0.05 and stimulation games educational tool with gross motor development fisher exact p-value=0.002<0.05. there is a relationship between stimulation games educational tool with the development of fine and gross motor pre-school age childreen. Keywords : Games Educational Tool, Development, Motor Coarse, Fine motor skills, pre-school age children.

Estimating Relative Risk from Heterogeneous Strata

1988 ◽  
Vol 27 (03) ◽  
pp. 118-124 ◽  
Author(s):  
W. Ahlborn ◽  
H.-J. Tuz ◽  
K. Überla
Keyword(s):  
Relative Risk ◽  
Cohort Studies ◽  
Risk Measures ◽  
Logistic Models ◽  
Case Control ◽  
Asymptotic Distributions ◽  
Weight Functions ◽  
Risk Indicator ◽  
Case Control Studies ◽  
Special Cases

SummaryThe uncritical use of risk estimators can lead to serious bias. The estimation of overall risk ratios for heterogeneous strata and the weights used have been discussed recently. This paper starts with the definition of relative risk in the population, considering heterogeneous strata and a cofactor, using weight functions. From this general formula four different weight functions leading to four different overall measures of relative risk (RR1, RR1, RR3, RR4 ) are. derived as special cases. The estimability of the parameters in relation to the underlying sampling design is investigated. Consistent estimators are provided and the asymptotic distributions of the estimators are given for prospective cohort studies, case control studies with fixed strata and case control studies with given sample sizes. For some of the estimates the . asymptotic variances are given. It is shown that for case control studies with fixed strata neither the Mantel-Haenszel estimator nor another estimator of this class is consistent. An extension to more than two risk levels is provided and the relationships between various risk measures and other implications are commented on. A way is described to improve risk estimation by using information from the population. An example for cohort studies is given. Generally we propose to use RR3 , which lies between RR1 and RR2 and can be estimated more precisely using the sometimes available distribution of the cofactor in the population. If the relative risk across strata is heterogeneous, logistic models for the construction of a single risk indicator have some drawbacks.

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