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Stata 12 graphics

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STATA 12 Graphics is a data visualization tool that allows users to create a variety of graphs and charts to effectively represent their data. The software provides a range of graphical options, including scatter plots, line graphs, bar charts, and histograms, among others. STATA 12 Graphics enables users to customize the appearance of their visualizations, making it a versatile tool for data analysis and presentation.

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5 protocols using stata 12 graphics

1

Genotype-Mortality Associations in Chronic Conditions

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General linear models were used to compare age-adjusted indirect measurements between groups, and logistic models were used to compare the age-adjusted direct measurements. Cox proportional models were used to assess the association of the PIK3R1 genotype with mortality stratified by disease status, such as by CVD, diabetes, and cancer, and by chronic conditions defined by the presence of any of these. The Cox proportional hazard assumption was tested for each Cox model. The effect of interaction of disease with the PIK3R1 genotype on mortality was tested in the Cox model. All statistical analyses were performed using the Statistical Analysis System version 9. 4 [20] . Figures were generated using STATA 12 Graphics [21] .
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2

Genetic variants and mortality risk

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General linear models were used to compare age-adjusted indirect measurements between groups, and logistic models were used to compare the age-adjusted direct measurements. Cox proportional models were used to assess the association of MAP3K5 for various genetic models on mortality stratified by disease status, such as by diabetes, by hypertension, by CHD, and by any of CHD, diabetes, or hypertension. The Cox proportional hazard assumption was tested for each Cox model. The effect of interaction of disease with MAP3K5 genotype on mortality was tested in the Cox model. All statistical analyses were performed using the Statistical Analysis System version 9.4 [22 ]. Figures were generated using STATA 12 Graphics [23 ].
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3

Genotype-Based Mortality Risk Models

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General linear models were used to compare age-adjusted indirect measurements between groups, and logistic models were used to compare the age-adjusted direct measurements. Cox proportional models were used to assess the association of FOXO3 minor-allele carriers with mortality stratified by disease status, such as by CHD, by diabetes, by hypertension, and by chronic conditions defined by presence of any of CHD, diabetes, or hypertension. The Cox proportional hazard assumption was tested for each Cox model. The effect of interaction of disease with FOXO genotype on mortality was tested in the Cox model. All statistical analyses were performed using the Statistical Analysis System version 9.4 [39 ]. Figures were generated using the STATA 12 Graphics [40 ].
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4

Genetic Influence on Longevity and Disease Associations

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General linear models were used to compare age-adjusted indirect measurements between groups according to hypertension, CHD, stroke, diabetes or cancer status and FLT1 genotype. Logistic models were used to compare the age-adjusted direct measurements. Cox proportional hazards models assessed the association of genotype of FLT1 with longevity using 4 genetic models; namely, major allele recessive (GG) vs other (GC, CC); heterozygote (GC) vs other (GG, CC), minor allele homozygote (CC) vs. other (GG, GC), and the additive model (number of C alleles) in which the combined effect of alleles is equal to the sum of their individual effects. The interaction of genotypes with chronic diseases such as hypertension, CHD, stroke, diabetes, and cancer was evaluated for these 4 gene models. If an interaction was significant after correction for multiple comparisons by the Bonferroni-Holm method [36 ], stratified analyses were then performed for genotype effect on mortality based on that gene model by that disease condition. Survival curves were generated using a Cox proportional hazard model adding an interaction term of FLT1 genotype with disease. All statistical analyses were performed using the Statistical Analysis System version 9.4 [37 ]. Figures were generated using STATA 12 Graphics [38 ].
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5

Genotype-Mortality Association in Chronic Diseases

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General linear models were used to compare age-adjusted indirect measurements between groups, and logistic models was used to compare the age-adjusted direct measurements. Cox proportional models were used to assess the association of GHR for 3 genetic models – namely, AA vs AG/GG, AG vs AA/GG, and GG vs AA/AG – on mortality stratified by disease status, such as by diabetes, by hypertension, by CHD, and by cancer. The effects of the genotype on mortality were corrected for multiple tests using by the Bonferroni method. The significant genetic model was selected and used in the analyses. The Cox proportional hazard assumption was tested for each Cox model. The effect of interaction of disease with GHR genotype on mortality was tested in the Cox model. All statistical analyses were performed using the Statistical Analysis System version 9.4 [36 ]. Figures were generated using STATA 12 Graphics [37 ].
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