紅茶 asked in 社會與文化語言 · 1 decade ago

有關統計方式 英翻中 請英文高手幫忙修改

The association between baseline coffee intake and incident hypertension as defined above was assessed among those who did not have hypertension at baseline as defined above.

Logistic regression was used with presence of persistent hypertension (yes or no) as the dependent variable and baseline coffee intake

and confounders as independent variables. Furthermore, effects of changes in coffee intake as a predictor of change of blood pressure were examined.

A repeated-measures analysis with time-varying covariates was used with changes between repeated blood pressure measurements as dependent variables and time-varying changes in coffee intake and confounders as independent variables. In all analyses, we adjusted for the following possible confounders: age, sex, body height and weight, smoking,alcohol intake, tea intake, educational level, occupational status, and total energy intake.

All analyses were expressed as measures of association with corresponding 95% CIs, regarding intervals not including the respective null values as statistically significant. Analyses were performed by using SPSS version 11.0 or SAS Proc Mixed for repeated-measures analysis (SPSS Inc, Chicago, IL).

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以下是自翻的↓

攝取咖啡和高血壓罹患率有相關性的as defined above was assessed among those who did not have hypertension at baseline as defined above.羅吉斯迴歸是使用在持續性高血壓出現(yes or no)作為因變數和攝取咖啡和confounders 作為自變數.此外,改變攝取咖啡的影響和血壓改變來檢驗。重複測量分析和時變性共變數 在反覆測血壓作為因變數和攝取咖啡時變性變化和confounders 作為自變數。總分析裡,調整其次可能的confounders :年齡、性別、身高、體重、抽菸、酒精攝取、攝取茶、教育程度、職業地位和總熱量攝取。全部分析表示出測量與95%CI有符合相關,關於間期不包含各無效值/空值作為統計上有效數字。反覆測量分析使用SPSS version 11.0 or SAS Proc Mixed(SPSS Inc, Chicago, IL)。

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2 Answers

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  • ?
    Lv 7
    1 decade ago
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    The association between baseline coffee intake and incident hypertension as defined above was assessed among those who did not have hypertension at baseline as defined above.

    咖啡基本攝取量和(如上所定義的)原發性高血壓兩者間的關連是以在(如上所定義的)咖啡基本攝取量下並無高血壓的一群人來做評量的.

    Logistic regression was used with presence of persistent hypertension (yes or no) as the dependent variable and baseline coffee intake and confounders as independent variables. Furthermore, effects of changes in coffee intake as a predictor of change of blood pressure were examined.

    以咖啡基本攝取量及干擾因素為自變數並以持續性高血壓出現與否(yes or no)為因變數來進行羅吉斯迴歸分析。此外,也審視了改變咖啡攝取量對血壓變化的預測能力。

    A repeated-measures analysis with time-varying covariates was used with changes between repeated blood pressure measurements as dependent variables and time-varying changes in coffee intake and confounders as independent variables. In all analyses, we adjusted for the following possible confounders: age, sex, body height and weight, smoking,alcohol intake, tea intake, educational level, occupational status, and total energy intake.

    以因時間而變化的咖啡攝取量之變化量及干擾因素為自變數並以反覆測量血壓的變化量作為因變數進行以時間共變項(time-varying covariates) 的重複測驗分析(Repeated Measures Analysis) 。所有的分析我們均對下列可能的干擾因素予以調整。可能的干擾因素包括:年齡、性別、身高、體重、抽菸、酒精攝取量、茶攝取量、教育程度、職業狀態及總攝取熱量。

    All analyses were expressed as measures of association with corresponding 95% CIs, regarding intervals not including the respective null values as statistically significant. Analyses were performed by using SPSS version 11.0 or SAS Proc Mixed for repeated-measures analysis (SPSS Inc, Chicago, IL).

    對於期間內無顯著統計意義的各別虛無值時, 所有的分析之相關程度係以在95%信賴區間內所測得的。反覆測量分析係以SPSS version 11.0 or SAS Proc Mixed(SPSS Inc, Chicago, IL) 來進行。

  • 1 decade ago

    之間的關聯基準事件的咖啡攝入量和高血壓的定義上述評估這些誰沒有高血壓基線上面界定。

    Logistic回歸是使用存在持續高血壓(是或否)為因變量和基線咖啡攝入量

    和混淆作為獨立的變量。此外,變化的影響咖啡的攝入量作為預測的變化血壓檢查。

    阿重複測量分析時變協變量的變化是使用重複之間血壓測量作為因變量,並隨時間變化的變化,咖啡的攝入和混淆作為獨立的變量。在所有的分析,我們調整了以下可能的混淆:年齡,性別,身高,體重,吸煙,飲酒,茶的攝入,教育程度,職業地位,總能量攝入。

    所有的分析,表達了措施與相應的95 %獨聯體,就間隔不包括NULL值分別為統計學意義。所完成的分析用SPSS 11.0版或SAS採用混合的重複測量分析( SPSS軟件公司,伊利諾伊州芝加哥) 。

    Source(s): 路過
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