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GUSTA ME
Home
Exploration
Notes on data structure
Visualisations
Why multivariate analysis?
(Dis)similarity-based methods
BIOENV
Cluster analysis
Hierarchical cluster analysis
Non-hierarchical cluster analysis
Cluster analysis & ordination
Non-metric multidimensional scaling
Principal coordinates analysis
SIMPER
Constrained analyses
Canonical correlation analysis
Canonical Correspondence Analysis
Partial Canonical Correspondence Analysis
Multiple linear regression
Multiple regression on (dis)similarity matrices
Path analysis
Redundancy Analysis
Distance-based redundancy analysis
Partial redundancy analysis
Variation partitioning
Discrimination
Linear discriminant analysis
Multiple discriminant analysis
Hypothesis tests
ANOSIM
Hotelling's T-squared test
MANOVA
NPMANOVA
SIMPROF
The Mantel test
Partial Mantel test
Indirect gradient analysis
Correspondence Analysis
Detrended correspondence analysis
Principal Components Analysis
Other methods
Factor analysis
Procrustes analysis
Reference
(Dis)similarity & distance
Data transformations
Distributions
Meta-analysis
Ranked data
Resampling
Permutation
Residuals
Variable types
Spatial analysis
Principal coordinates of neighbour matrices
The GUSTA ME Blog
hello world!
Walkthroughs
Comparison of Bacterial Communities in Sands and Water at Beaches with Bacterial Water Quality Violations
Diversity and dynamics of rare and of resident bacterial populations in coastal sands
Soil characteristics more strongly influence soil bacterial communities than land-use type
Spatial and Temporal Variation in a Caribbean Herbivorous Fish Assemblage
The energy–diversity relationship of complex bacterial communities in Arctic deep-sea sediments
The influence of habitat heterogeneity on freshwater bacterial community composition and dynamics
Warnings
Autocorrelation
Data dredging
Heteroscedasticity
Missing data
Multicollinearity and confounding variables
Multiple testing
Outliers
Overdetermination
Pseudoreplication
Wizards
(Dis)similarity wizard
Q mode data
Asymmetrical Q mode
Measures for presence/absence and ordinal data
Measures for quantitative and semiquantitative data
Measures for normalised abundance or abundances rated on a scale
Measures for raw abundance data
Measures for differentially weighted, raw abundance data
Measures for equally weighted, raw abundance data
Normalised abundance data without object-standardisation
Object-standardised, normalised abundance data
Probabilistic measures for raw abundance data
Symmetrical Q mode
Association between groups of objects
Association between individual objects
Associations with no partial similarity
Associations with partial similarities
Associations for objects described by qualitative and inhomogeneous variables
Associations for objects described by quantitative and homogeneous variables
R mode data
R mode measures for abundance data
R mode measures for normalised abundance data
R mode measures for raw abundance data
R mode measures for environmental data
R mode measures for linear environmental variables
R mode measures for ordered environmental variables
R mode measures for qualitative and non-monotonic variables
Constrained analyses wizard
Response distribution
Consider CCA
Consider redundancy analysis
Consider the Mantel test or Procrustes analysis
Data distribution
(Dis)similarity-based exploration
Linear exploratory methods
Hypothesis testing
(Dis)similarity-based hypothesis testing
Hypothesis testing: association of variables
Hypothesis testing: association with (dis)similarity data
Hypothesis testing: association with raw data
Hypothesis testing: differences between groups
Hypothesis testing: differences between groups expressed by (dis)similarity
Hypothesis testing: differences between groups expressed by raw data
Raw-data hypothesis testing
Raw data or distance matrix?
Screening
GUSTA ME
Home
Exploration
Notes on data structure
Visualisations
Why multivariate analysis?
(Dis)similarity-based methods
BIOENV
Cluster analysis
Hierarchical cluster analysis
Non-hierarchical cluster analysis
Cluster analysis & ordination
Non-metric multidimensional scaling
Principal coordinates analysis
SIMPER
Constrained analyses
Canonical correlation analysis
Canonical Correspondence Analysis
Partial Canonical Correspondence Analysis
Multiple linear regression
Multiple regression on (dis)similarity matrices
Path analysis
Redundancy Analysis
Distance-based redundancy analysis
Partial redundancy analysis
Variation partitioning
Discrimination
Linear discriminant analysis
Multiple discriminant analysis
Hypothesis tests
ANOSIM
Hotelling's T-squared test
MANOVA
NPMANOVA
SIMPROF
The Mantel test
Partial Mantel test
Indirect gradient analysis
Correspondence Analysis
Detrended correspondence analysis
Principal Components Analysis
Other methods
Factor analysis
Procrustes analysis
Reference
(Dis)similarity & distance
Data transformations
Distributions
Meta-analysis
Ranked data
Resampling
Permutation
Residuals
Variable types
Spatial analysis
Principal coordinates of neighbour matrices
The GUSTA ME Blog
hello world!
Walkthroughs
Comparison of Bacterial Communities in Sands and Water at Beaches with Bacterial Water Quality Violations
Diversity and dynamics of rare and of resident bacterial populations in coastal sands
Soil characteristics more strongly influence soil bacterial communities than land-use type
Spatial and Temporal Variation in a Caribbean Herbivorous Fish Assemblage
The energy–diversity relationship of complex bacterial communities in Arctic deep-sea sediments
The influence of habitat heterogeneity on freshwater bacterial community composition and dynamics
Warnings
Autocorrelation
Data dredging
Heteroscedasticity
Missing data
Multicollinearity and confounding variables
Multiple testing
Outliers
Overdetermination
Pseudoreplication
Wizards
(Dis)similarity wizard
Q mode data
Asymmetrical Q mode
Measures for presence/absence and ordinal data
Measures for quantitative and semiquantitative data
Measures for normalised abundance or abundances rated on a scale
Measures for raw abundance data
Measures for differentially weighted, raw abundance data
Measures for equally weighted, raw abundance data
Normalised abundance data without object-standardisation
Object-standardised, normalised abundance data
Probabilistic measures for raw abundance data
Symmetrical Q mode
Association between groups of objects
Association between individual objects
Associations with no partial similarity
Associations with partial similarities
Associations for objects described by qualitative and inhomogeneous variables
Associations for objects described by quantitative and homogeneous variables
R mode data
R mode measures for abundance data
R mode measures for normalised abundance data
R mode measures for raw abundance data
R mode measures for environmental data
R mode measures for linear environmental variables
R mode measures for ordered environmental variables
R mode measures for qualitative and non-monotonic variables
Constrained analyses wizard
Response distribution
Consider CCA
Consider redundancy analysis
Consider the Mantel test or Procrustes analysis
Data distribution
(Dis)similarity-based exploration
Linear exploratory methods
Hypothesis testing
(Dis)similarity-based hypothesis testing
Hypothesis testing: association of variables
Hypothesis testing: association with (dis)similarity data
Hypothesis testing: association with raw data
Hypothesis testing: differences between groups
Hypothesis testing: differences between groups expressed by (dis)similarity
Hypothesis testing: differences between groups expressed by raw data
Raw-data hypothesis testing
Raw data or distance matrix?
Screening
More
Home
Exploration
Notes on data structure
Visualisations
Why multivariate analysis?
(Dis)similarity-based methods
BIOENV
Cluster analysis
Hierarchical cluster analysis
Non-hierarchical cluster analysis
Cluster analysis & ordination
Non-metric multidimensional scaling
Principal coordinates analysis
SIMPER
Constrained analyses
Canonical correlation analysis
Canonical Correspondence Analysis
Partial Canonical Correspondence Analysis
Multiple linear regression
Multiple regression on (dis)similarity matrices
Path analysis
Redundancy Analysis
Distance-based redundancy analysis
Partial redundancy analysis
Variation partitioning
Discrimination
Linear discriminant analysis
Multiple discriminant analysis
Hypothesis tests
ANOSIM
Hotelling's T-squared test
MANOVA
NPMANOVA
SIMPROF
The Mantel test
Partial Mantel test
Indirect gradient analysis
Correspondence Analysis
Detrended correspondence analysis
Principal Components Analysis
Other methods
Factor analysis
Procrustes analysis
Reference
(Dis)similarity & distance
Data transformations
Distributions
Meta-analysis
Ranked data
Resampling
Permutation
Residuals
Variable types
Spatial analysis
Principal coordinates of neighbour matrices
The GUSTA ME Blog
hello world!
Walkthroughs
Comparison of Bacterial Communities in Sands and Water at Beaches with Bacterial Water Quality Violations
Diversity and dynamics of rare and of resident bacterial populations in coastal sands
Soil characteristics more strongly influence soil bacterial communities than land-use type
Spatial and Temporal Variation in a Caribbean Herbivorous Fish Assemblage
The energy–diversity relationship of complex bacterial communities in Arctic deep-sea sediments
The influence of habitat heterogeneity on freshwater bacterial community composition and dynamics
Warnings
Autocorrelation
Data dredging
Heteroscedasticity
Missing data
Multicollinearity and confounding variables
Multiple testing
Outliers
Overdetermination
Pseudoreplication
Wizards
(Dis)similarity wizard
Q mode data
Asymmetrical Q mode
Measures for presence/absence and ordinal data
Measures for quantitative and semiquantitative data
Measures for normalised abundance or abundances rated on a scale
Measures for raw abundance data
Measures for differentially weighted, raw abundance data
Measures for equally weighted, raw abundance data
Normalised abundance data without object-standardisation
Object-standardised, normalised abundance data
Probabilistic measures for raw abundance data
Symmetrical Q mode
Association between groups of objects
Association between individual objects
Associations with no partial similarity
Associations with partial similarities
Associations for objects described by qualitative and inhomogeneous variables
Associations for objects described by quantitative and homogeneous variables
R mode data
R mode measures for abundance data
R mode measures for normalised abundance data
R mode measures for raw abundance data
R mode measures for environmental data
R mode measures for linear environmental variables
R mode measures for ordered environmental variables
R mode measures for qualitative and non-monotonic variables
Constrained analyses wizard
Response distribution
Consider CCA
Consider redundancy analysis
Consider the Mantel test or Procrustes analysis
Data distribution
(Dis)similarity-based exploration
Linear exploratory methods
Hypothesis testing
(Dis)similarity-based hypothesis testing
Hypothesis testing: association of variables
Hypothesis testing: association with (dis)similarity data
Hypothesis testing: association with raw data
Hypothesis testing: differences between groups
Hypothesis testing: differences between groups expressed by (dis)similarity
Hypothesis testing: differences between groups expressed by raw data
Raw-data hypothesis testing
Raw data or distance matrix?
Screening
Measures for equally weighted, raw abundance data
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