Female
subjects
have
been
historically
excluded
from
biomedicine
and
other
related
areas
of
study
[1].
Such
exclusion
has
disadvantaged
females
prevented
a
fuller
understanding
biology.
Therefore,
in
2016,
the
National
Institute
Health
(NIH)
mandated
that
all
NIH-funded
animal
human
studies
consider
sex
as
biological
variable
(e.g.,
[2]).
Yet,
not
welcomed
with
open
arms,
most
likely
because
many
researchers
believe
they
need
to
increase
overall
sample
size
two
sexes
compared
using
only
one
Recently,
Philips
colleagues
published
PLoS
Biology
article
titled
“Statistical
simulations
show
scientists
by
default
when
including
both
vivo
studies”
[3].
As
indicated
their
title,
authors
concluded
recommended
no
sexes,
which
was
based
on
set
exploring
simple
but
–
claim
scenario.
Their
conclusion
is
great
news
for
who
feared
coping
increased
experiment
sizes
costs.
Bingöl Üniversitesi Sağlık Dergisi,
Год журнала:
2024,
Номер
5(1), С. 242 - 244
Опубликована: Март 26, 2024
Bu
çalışma,
sağlık
bilimlerindeki
araştırmalarda
sıklıkla
kullanılan
istatistiksel
analiz
sonuçları
ile
klinik
uygunluk
arasındaki
ilişkiyi
değerlendirmeyi
amaçlamıştır.
İstatistiksel
anlamlılık,
bir
sonucun
tesadüfi
olup
olmadığını
değerlendiren
ölçütken,
bulgunun
gerçek
dünya
koşullarında
önemli
ya
da
yararlı
ifade
etmektedir.
Araştırmacılar,
olarak
anlamlı
olmasının
yanı
sıra,
açıdan
uygun
değerlendirmelidir.
Ayrıca
araştırmacılar
etki
büyüklüğü,
kapsamlı
literatür
incelemesi
gibi
konulara
özellikle
dikkat
etmelidir.
Sonuç
sahada
uygulanacak
girişimlerde
istatistik
anlamlılık
önemlidir.
Ancak
tek
başına
yeterli
değildir.
Dolayısıyla
bilimsel
araştırmalardan
elde
edilen
sonuçlar
hem
yönünden
de
değerlendirilmelidir.
Nature Ecology & Evolution,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 26, 2024
Abstract
Despite
the
growing
concerns
about
replicability
of
ecological
and
evolutionary
studies,
no
results
exist
from
a
field-wide
replication
project.
We
conduct
large-scale
in
silico
project,
leveraging
cutting-edge
statistical
methodologies.
Replicability
is
30%–40%
for
studies
with
marginal
significance
absence
selective
reporting,
whereas
presenting
‘strong’
evidence
against
null
hypothesis
H
0
>70%.
The
former
requires
sevenfold
larger
sample
size
to
reach
latter’s
replicability.
call
change
planning,
conducting
publishing
research
towards
transparent,
credible
replicable
ecology
evolution.
Female
subjects
have
been
historically
excluded
from
biomedicine
and
other
related
areas
of
study
[1].
Such
exclusion
has
disadvantaged
females
prevented
a
fuller
understanding
biology.
Therefore,
in
2016,
the
National
Institute
Health
(NIH)
mandated
that
all
NIH-funded
animal
human
studies
consider
sex
as
biological
variable
(e.g.,
[2]).
Yet,
not
welcomed
with
open
arms,
most
likely
because
many
researchers
believe
they
need
to
increase
overall
sample
size
two
sexes
compared
using
only
one
Recently,
Philips
colleagues
published
PLoS
Biology
article
titled
“Statistical
simulations
show
scientists
by
default
when
including
both
vivo
studies”
[3].
As
indicated
their
title,
authors
concluded
recommended
no
sexes,
which
was
based
on
set
exploring
simple
but
–
claim
scenario.
Their
conclusion
is
great
news
for
who
feared
coping
increased
experiment
sizes
costs.
