Trends analysis in diabetes mellitus diagnosis according to relative handgrip strength. by Yeo Ju Sohn (18536198)

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Model prediction error trend chart. by Hongqi Wang (2208238)

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Illustration of the innovative trend analysis (ITA) method. by Asnake Adane (19935018)

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Trends in adolescent fertility rates in Sierra Leone, 2008–2019. by Augustus Osborne (15249788)

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General characteristics of relative handgrip strength at baseline. by Yeo Ju Sohn (18536198)

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This dataset includes detailed information for 22,016 individuals. by Yeo Ju Sohn (18536198)

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Flow diagram of participants meeting the inclusion and exclusion criteria. by Yeo Ju Sohn (18536198)

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Initial participants by wave*. by Yeo Ju Sohn (18536198)

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These files contain the STATA program codes used in the study. by Yeo Ju Sohn (18536198)

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Generalized estimating equation model covariance structure analysis. by Yeo Ju Sohn (18536198)

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Raw dataset collected from the KLoSA from 2006 to 2020. by Yeo Ju Sohn (18536198)

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General characteristics of research participants. by Yeo Ju Sohn (18536198)

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Generalized estimation equation model analysis of diabetes mellitus incidence according to relative handgrip strength. by Yeo Ju Sohn (18536198)

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Proportion of the increase (green) or decrease (red) in forest cover in areas with different fire recurrences in Africa, according to the Mann-Kendall test and statistically signif... by Oswaldo Maillard (20660661)

Innovative trend analysis of MAM rainfall (1981–2022). by Asnake Adane (19935018)

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Innovative trend analysis of JJA rainfall (1981–2022). by Asnake Adane (19935018)

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Innovative trend analysis of annual rainfall (1981–2022). by Asnake Adane (19935018)

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Innovative trend analysis of SON rainfall (1981–2022). by Asnake Adane (19935018)

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Innovative trend analysis of DJF rainfall (1981–2022). by Asnake Adane (19935018)

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Parallel trend test. by Pu Miao (12886949)

“…During this lag period, the effect on the number of patent declines by 8.475% to 28.283%, while the impact on the number of citations of patents decreases by 55.696% to 73.214%. (4) The significant promotional effect of science and technology talent policies is most pronounced in non-state-owned enterprises and those with high R&D investment, but such policies do not have a notable impact on state-owned enterprises or those with low R&D investment. …”