unbal.two.factor.rep

Measure of (unadjusted) repeatability with missing values

internal

Accurate estimates of the diets of predators are required
in many areas of ecology, but for many species current methods are
imprecise, limited to the last meal, and often biased. The diversity
of fatty acids and their patterns in organisms, coupled with the
narrow limitations on their biosynthesis, properties of digestion in
monogastric animals, and the prevalence of large storage reservoirs of
lipid in many predators, led to the development of quantitative
fatty acid signature analysis (QFASA) to study predator diets.

Connie Stewart

QFASA

Quantitative Fatty Acid Signature Analysis

Sara Iverson

Chris Field

Don Bowen

Wade Blanchard

Shelley Lang

Justin Kamerman

Hongchang Bao

Holly Steeves

Jennifer McNichol

Tyler Rideout

unbal.two.factor.rep function

<dl><dt>dataset</dt>
<dd>data frame of diet estimates. Columns 1 and 2 of
<code>dataset</code> must be the first and second factors in your two factor
ANOVA model where column 1 specifies the predator and column 2 the
year, season, etc... Missing values are allowed.</dd>
<dt>k.est.meth</dt>
<dd>default is 1 (harmonic mean). See details below.</dd>
<dt>gamma</dt>
<dd>needed to compute CS distance. Default is 1.</dd></dl>

Arguments

Measure of (unadjusted) repeatability with missing values — unbal.two.factor.rep

<dl>

<dt>dataset</dt>
<dd>data frame of diet estimates. Columns 1 and 2 of
<code>dataset</code> must be the first and second factors in your two factor
ANOVA model where column 1 specifies the predator and column 2 the
year, season, etc... Missing values are allowed.</dd>


<dt>k.est.meth</dt>
<dd>default is 1 (harmonic mean). See details below.</dd>


<dt>gamma</dt>
<dd>needed to compute CS distance. Default is 1.</dd>

</dl>

Measure of (unadjusted) repeatability with missing values

unbal.two.factor.rep: Measure of (unadjusted) repeatability with missing values

Description

Usage

Value

Arguments

Details