Goals of ethics review
any human research must go through the IRB
- Prevent gross ethical violations
- Correct for blind spots
History of US regulations
1974 National research act protection of biomedical and behavioral human subjects
1979 Belmont report
1991 Common Rule–set of federal regulations
Belmont Principles
- Respect–informed consent, time, procedures, risks and benefits, voluntary, NO COERCION
- Beneficence–research must do good for someone. Medigate risk and justify it. Confidentiality
- Justice–risks and rewards. Not equal. researchers reaped benefit from vulnerable people’s risk
IRBs
every IRB must be federally registered
- 2 kinds. A promise to govt and set up our own IRB
- if only the first, you can use another institution’s IRB
IRB membership
- represent all three divisions. natural, social, humanities
- community members in our case the bishop and the Sanford employee.
IRB duties
- review every proposal. not everything is research.
- only wide generalized knowledge, not classwork, history, stuff for augie.
IRB guidance
regulations–who is the primary investigator?
policy
judgement
IRB process
-intial proposal (form)
submit all materials like flyers and informed consent forms
-exempt, expedited and full
expedited is minimal risk encountered in daily life
-reviewers
checklists and need some mods
further requests to primary investigators
-final decision–can be denied
-need to follow up. Have to say what happened and report any adverse effects. must submit another request to continue the study
Guidelines for figures
- simplify without falsifying data
- graph/table
- brevity and clarity
- note prior conventions
Tables
-need specific data points
-useful for exact comparisons
-stand on its own
-show data and possible manipulations
%s, total, means, averages
-define abbreviations at bottom
-units at top
-limit number of things in the table
-align stuff
-dont go crazy with decimals
-verify all data
-accurate use of symbols
Bar Charts
- less numerically specific
- examine differences rather than trends
- compare size, magnitude
- bars need to be wider than the spaces between them
Line graphs
-not numerically specific
-demonstrate movement, changing trends
-generally over time/concentrations
-regular intervals with two axis and units
don’t do line patterns, vary symbols.
Graph parts
- legend or key
- label at the bottom
- units on axis
- use color and symbols to your advantage!
Figures general guidelines
- Is a figure needed?
- no top title
- limit 3-5 curves, 6-8 bars
- label axis with units
- start scales at 0 otherwise be clear about what youre doing
- legends and keys
- should stand alone
Referring
- every table or figure should be referred to in the text
- whats interesting about the figure? not just see results in blah blah
How do we determine experimental unit and the replicate?
- experimental unit stands alone
- replicates are related in some way
experimental unit
- physical entity which can be assigned a treatment at random
- can receive either the treatment or not
Pseudoreplication
-treating multiple measurements on the same units as if they are measurements on independent units
What is replication?
the smallest experimental unit to which a treatment is independently applied
treatments must be repeated or independent experimental units in order to avoid pseudoreplication
-how many depends on the natural variation of the data set
MUST HAVE
- replication
each treatment tested on more than one experimental unit - randomization
experimental units are allocated to treatments at random
Example: grass was assigned to 3 different trays and 54 plants were planted
- sample is 3. n = 3.
- randomize by moving around in the growth chamber
Principle component analysis
- data reduction technique
- only multivariate technique we will look at
- reduce to see what mainly controls data variation
Data reduction
- sum of data with many p variables by smaller set of k derived (synthetic, composite) variables
- balancing act between clarity of representation and ease of understanding. If you oversimplify you may lose relevant data
- Pearson and Hotelling in ecology developed
- most widely known and used “standard” tests
- matrix of n objects by p variables which may be correlated
- m components ranked by variability
Principle components
- ranked by how much variability they explain.
- NOT related to each other, not linearly correlated
- composite variables, combo of variables
