The main objective of this study is to divide a number of colorectal cancer cases into subgroups based on their molecular features using cluster analysis. The data used is supplied by a research group at Pathology, the Department of Medical Biosciences, Umeå University, and consists, after some preparation, of 455 observations which is a larger data set than many similar studies. The molecular variables that the clustering is based on are CIMP (CpG Island Methylator Phenotype), MSI (Micro Satellite Instability), BRAF- and KRAS-mutations. These are categorical variables and consequently the clustering method used is PAM (Partitioning Around Medoids) which is particularly useful with data on diverse variable level. The final analysis results in four subgroups that are represented by different combinations of attributes on the aforementioned variables.

The main objective of this study is to divide a number of colorectal cancer cases into subgroups based on their molecular features using cluster analysis. The data used is supplied by a research group at Pathology, the Department of Medical Biosciences, Umeå University, and consists, after some preparation, of 455 observations which is a larger data set than many similar studies. The molecular variables that the clustering is based on are CIMP (CpG Island Methylator Phenotype), MSI (Micro Satellite Instability), BRAF- and KRAS-mutations. These are categorical variables and consequently the clustering method used is PAM (Partitioning Around Medoids) which is particularly useful with data on diverse variable level. The final analysis results in four subgroups that are represented by different combinations of attributes on the aforementioned variables.

The main objective of this study is to divide a number of colorectal cancer cases into subgroups based on their molecular features using cluster analysis. The data used is supplied by a research group at Pathology, the Department of Medical Biosciences, Umeå University, and consists, after some preparation, of 455 observations which is a larger data set than many similar studies. The molecular variables that the clustering is based on are CIMP (CpG Island Methylator Phenotype), MSI (Micro Satellite Instability), BRAF- and KRAS-mutations. These are categorical variables and consequently the clustering method used is PAM (Partitioning Around Medoids) which is particularly useful with data on diverse variable level. The final analysis results in four subgroups that are represented by different combinations of attributes on the aforementioned variables.

The main objective of this study is to divide a number of colorectal cancer cases into subgroups based on their molecular features using cluster analysis. The data used is supplied by a research group at Pathology, the Department of Medical Biosciences, Umeå University, and consists, after some preparation, of 455 observations which is a larger data set than many similar studies. The molecular variables that the clustering is based on are CIMP (CpG Island Methylator Phenotype), MSI (Micro Satellite Instability), BRAF- and KRAS-mutations. These are categorical variables and consequently the clustering method used is PAM (Partitioning Around Medoids) which is particularly useful with data on diverse variable level. The final analysis results in four subgroups that are represented by different combinations of attributes on the aforementioned variables.

Vi fick av företaget Cardo i uppdrag att analysera deras mentorprogram, vilket ingick i deras managementprogram, CIMP 2005. Då deltagarna hade olika bakgrund och erfarenhet och därmed olika förutsättningar, bestod vårt uppdrag av att analysera och finna eventuella skillnader mellan deltagare som fått utbildning och handledning jämfört med dem som inte fått detta. Vårt syfte var att med utgångspunkt i deltagarnas upplevelser av mentorprogrammet, analysera deltagarnas reflektiva lärande, utifrån både ett adept- och mentorperspektiv. Med denna utgångspunkt valde vi att använda oss av ett kvalitativt angreppssätt med en empirisk och en teoretisk del. Den empiriska delen inleddes med en kort e-postintervju till samtliga deltagare.