There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Akihiro Hirakawa |
| Institution: | Tokyo Medical and Dental University |
| Department: | Department of Clinical Biostatistics |
| Country: | |
| Proposed Analysis: | In this study, we develop new statistical methodologies to longitudinal trajectory modeling for cognitive function scales such as MMSE and ADAS-cog using the ADNI data. Based on the proposed methods, we explore the major source of variations of cognitive function scales. We also apply the proposed methods the cognitive data from the Japanese ADNI study. |
| Additional Investigators | |
| Investigator's Name: | Hiroyuki Sato |
| Proposed Analysis: | In this study, we develop new statistical methodologies to longitudinal trajectory modeling for cognitive function scales such as MMSE and ADAS-cog using the ADNI data. Based on the proposed methods, we explore the major source of variations of cognitive function scales. We also apply the proposed methods the cognitive data from the Japanese ADNI study. |
| Investigator's Name: | Ryoichi Hanazawa |
| Proposed Analysis: | In this study, we develop new statistical methodologies to longitudinal trajectory modeling for cognitive function scales such as MMSE and ADAS-cog using the ADNI data. Based on the proposed methods, we explore the major source of variations of cognitive function scales. We also apply the proposed methods the cognitive data from the Japanese ADNI study. |
| Investigator's Name: | Masanao Sasaki |
| Proposed Analysis: | In this study, we develop new statistical methodologies to longitudinal trajectory modeling for cognitive function scales such as MMSE and ADAS-cog using the ADNI data. Based on the proposed methods, we explore the major source of variations of cognitive function scales. We also apply the proposed methods the cognitive data from the Japanese ADNI study. |
| Investigator's Name: | Yosuke Shimizu |
| Proposed Analysis: | In this study, we develop new statistical methodologies to longitudinal trajectory modeling for cognitive function scales such as MMSE and ADAS-cog using the ADNI data. Based on the proposed methods, we explore the major source of variations of cognitive function scales. We also apply the proposed methods the cognitive data from the Japanese ADNI study. |
| Investigator's Name: | Masaya Watanabe |
| Proposed Analysis: | We investiage practice effects in cognitive function measures using ADNI data. |
