• Count data should not be treated they are dichotomous data.

    二分类数据计数资料处理

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  • For dichotomous data we calculated risk ratios (RR) and 95% confidence intervals (CI).

    针对二元性的资料我们计算了相对风险(RR)95%信赖区间(CI)。

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  • The standardised mean difference and relative risk were used for continuous data and dichotomous data comparisons, respectively.

    连续性数据二分的数据各自标准平均相对风险来比较

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  • The DSC data obtained are fitted to the integral, differential and exothermic rate equations by linear least-squares, iterative, combined dichotomous and least-squares methods, respectively.

    线性最小乘法迭代法以及二分法最小二乘法相结合方法积分方程微分方程放热速率方程拟合dsc数据

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  • Standardised or weighted mean differences were used to pool data for continuous outcomes and odds ratios were used to pool data for dichotomous outcomes, together with 95% confidence intervals.

    对于连续性结果变项使用标准化加权平均值差异来分析处理资料,而二分的结果变项则使用胜算95%信赖区间分析处理资料。

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  • For dichotomous outcomes, you will need to enter the number of events (in this case, the number of headaches) and the number of participants in each group. Enter the following data into the table.

    对于二分类变量结局来说,只需输入事件发生(例中,即发生头痛人数)的总人数。将下表数据输入表格中。

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  • Results are reported as odds ratios (OR) for dichotomous outcomes and weighted mean differences for continuous data.

    结果报告两分法OR呈现连续数据加权平均差别呈现。

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  • Results are reported as odds ratios (OR) for dichotomous outcomes and weighted mean differences for continuous data.

    结果报告两分法OR呈现连续数据加权平均差别呈现。

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