Note slide 8 Lectures : 18/4 + 22/4 + 25/4 + 27/4(first 22 ...
Transcript of Note slide 8 Lectures : 18/4 + 22/4 + 25/4 + 27/4(first 22 ...
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Note slide 8
Lectures : 18/4 + 22/4 + 25/4 + 27/4(first 22
min )
Notes written in pink color
Done by ; nursing lijan
FOUNDATIONS OFNURSING RESEARCH
Sixth Edition
CHAPTER
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Populations and
Samples
11
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Learning Objective One
Define Population And Sample
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Population
• Complete set of persons or objects
• Common characteristic
• Of interest to the researcher
مجتمع الدراسة
الباحث مهتم فيه ولاحقا بيطمح لانه يعمم النتائج عليهم
ما بقدر اعمل عليهم الدراسة لانه عددهم كبير
quantitative بيكون حجمه كبير ب
Qualitative بيكون الحجم قليل ب
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Sample
• Subset of a population
• Sample represents the population.
عينة الدراسة
لازم تكون ممثلة لمجتمع الدراسة وهي حزء منه
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Sample Selection
• Representation of the population
• Method for getting the sample
عشوائية ومنتظمة
• Sample size for the study
Depend if qualitative or quantitative
تعتمد عليها قوة البحث
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Sample Terms
• Element (participants )
– Single member of a population
• Sampling frame
– Listing of all elements
– Study sample
باحث بده يعمل بجثه على طلبة الجامعة الاردنية كلية :مثلا
التمريض فبييجي بحط كل الاسماء عورقة وهو بيصير يختار
منهم سواء اختيار عشوائي او حسب مميزات معينة وهيك بتكون
سهلت عالباحث الاختيار
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Learning Objective Two
Distinguish Between Target And
Accessible Population
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Population Terms
• Target population
• Accessible population
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Target Population
• Definition
– Entire group of people or objects
– People or objects meet designated set of
criteria.
– Generalization of the findings
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Accessible Population
• Definition
– Group of people or objects
– Researcher has access to them.
بقدر الباحث يوصلهم ومنهم بوخذ العينة تاعت الدراسة
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Population Importance
• Conclusions based on data
• Data from accessible population
• Decisions made from study results
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Learning Objective Three
Discuss Probability And Nonprobability
Sampling Procedures
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Types of Sampling Methods
• Probability
• Nonprobability
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Probability Sampling
• Uses random sampling procedures
• Selects sample from elements or members of population
• Types
– Simple
– Stratified
– Cluster
– Systematic
ة الدراسةبتعطي فرصة متساوية لكل شخص بجتمع الدراسة انه يكون ضمن عين•
لك هاد النوع افضل من النوع الثاني لانه قادر على تعميم النتائج لكن مع ذ•
السؤال البحثي هو يلي بحدد
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Nonprobability Sampling
• Uses nonrandom sampling procedures
• Selects sample from elements or members of population
• Types
– Convenience
– Snowballing
– Quota
– Purposive
باحث بده يعمل بحث على الاطفال يلي تعرضوا للاساءة فالباحث راح : مثلا
يدور على هاي الفئة من الناس
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Learning Objective Four
Compare Four Methods Of Probability
Sampling
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Probability Sampling
• Simple random
• Stratified
• Cluster
• Systematic
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Random Selection
• Key word in sample selection
• Every subject has an equal chance.
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Probability Sampling
• Allows researcher to estimate the chance
• Helps with inferential statistics with greater
confidence
• Gives the ability to generalize the findings
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Simple Random Sampling
• Type of probability sampling
• Importance of this sampling
– Equal chance of selection
– Independent chance of selection
هاد النوع الاكثر قوة واستخداما لكنه غير سهل
Sample frame احد الطرق للاختيار انه بعد ما نعمل
احط الاوراق يلي بتعبر عن المشاركين واختار منهم عشوائيا -1: انه
بستخدم جدول وبختار مربع معين بحيث يكون كل مربع بيمثل مشارك معين-2
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Advantages of
Simple Random Sampling
• Little knowledge of population is needed.
• Most unbiased of probability method
• Easy to analyze data and compute errors
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Disadvantages of
Simple Random Sampling
• Complete listing of population is
necessary.
• It is time consuming to use.
..بالكتاب مهم جدا اقراوه1-11جدول
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Steps for Simple Random Sampling
• Identify the accessible population or list of
elements
• Choose the method for getting the sample
• Note how easy it is through this example
– Names of elements on slips of paper
– Papers are placed into a hat.
– Individual draws a slip of paper.
– Individual continues until sample number is
met.
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Stratified Random Sampling
• Type of probability sampling
• Population is divided into subgroups or
strata.
• Simple random sample taken from each
strata
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Approaches for
Stratified Random Sampling
• Proportional stratified sampling
– Determine sampling fraction for each stratum
– Ensure that this stratum is equal
– Proportion in total population
• Disproportional stratified sampling
– Determine stratum is represented
– Used when strata are very unequal
– Note the key word disproportional
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Advantages of Stratified
Random Sampling (cont’d)
• Increases probability of being
representative
• Ensures adequate number of cases for
strata
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Disadvantages of
Stratified Random Sampling
• Requires accurate knowledge of
population
• May be costly to prepare stratified lists
• Statistics are more complicated.
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Cluster Random Stratified Sampling
• Large groups or clusters, not people, are
selected from population.
• Simple, stratified or systematic random
sampling may be used during each phase
of sampling.
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Cluster Random Stratified Sampling
• Cluster sampling is accomplished by dividing the
population into groups -- usually geographically. These
groups are called clusters or blocks. The clusters are
randomly selected, and each element in the selected
clusters are used.
• Stratified sampling also divides the population into
groups called strata. However, this time it is by some
characteristic, not geographically. For instance, the
population might be separated into males and females. A
sample is taken from each of these strata using either
random, systematic, or convenience sampling.
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Advantages of
Cluster Random Sampling
• Saves time and money
• Arrangements made with small number
sampling units
• Characteristics of clusters or population
can be estimated.
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Disadvantages of
Cluster Random Sampling
• Causes a larger sampling error
• Uses a more complicated statistic analysis
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Systematic Random Sampling
• Type of probability sampling
• Every kth element is selected.
• Process
– Obtain a listing of population
– Determine the sample size
– Determine the sampling interval (k = N/n)
– Select random starting point
– Select every kth element
الاختيار بيكون كل فترات منتظمة مثلا كل رابع شخص
لانها جدا مهمة K لازم نحدد ال
N= total population
N= sample size
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Ex : if population =1000 and sample size = 100
K=10
يلي بالقائمة 10يعني بختار كل عاشر شخص ولازم اول شخص اختاره يكون رقمه من اول
لانه لازم نختار 12فراح يكون رقم الشخص الثاني رقمه 2يعني لو كان رقم الشخص الاول
كل عاشر شخص
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Advantages of
Systematic Random Sampling
• Easy to draw sample
• Economical
• Time-saving technique
biase في شرطين مهمين لازم يتحققوا عشان ما يصير
1- population list
2-k
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Disadvantages of
Systematic Random Sampling
• Samples may be biased.
• After first sample is chosen, no longer
equal chance
ي اول شخص هو يلي بنطبق عليهم الاختيار العشوائي بس الباقk لا لانه راح تنطبق عليهم ال
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Learning Objective Five
Compare Methods Of Nonprobability
Sampling
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Nonprobability Sampling
• Sample elements are chosen
nonrandomly.
• Produces biased sample
• Each element of the population may not
be included in the sample.(no equal
chance )
• Restricts generalizations made about
study findings
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Nonprobability Sampling
• Convenience
• Snowballing
• Quota
• Purposive
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Convenience Sampling
• Chooses the most readily available subject or
object
• Does not guarantee that the subject or object is
typical of the population
بختارهم بالصدفة
سهلة وسريعة
ية باحث بده يوزع استبيان على طلبة كلية التمريض فراح عالكل: مثال
شخص اخذهم 20واول
المشكلة انه ممكن يلي اختارهم ممكن ما تكون ممثلة لمجتمع البحث
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Snowball Sampling
• Type of convenience sampling method
• Study subjects recruit other potential
subjects.
• May be called network sampling
• May find people reluctant to volunteer
انه باخذ مشارك وبحكيله اذا بعرف ناس اخرين عندهم نفس
التجربة وهو بيصير يدلنا عليهم
عدد المشاركين بكبر تدريجيا
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Quota Sampling
• Type of nonprobability sampling
• Researcher selects sample to reflect
characteristics.
• Similar to stratified but stratified use
random sample selection but quota use
convenous selection
• قسمنا المشاركين حسب الجنس وبعدها اخترنا اول : مثال quota امراة هاد هو 20
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Quota Sampling
• Age
• Gender
• Educational background
• Number of elements in each stratum
• Number is in proportion to size of total
population.
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Purposive Sampling
• Type of nonprobability sampling
• Researcher uses personal judgment in
subject selection.
• Each subject chosen is considered
representative of population.
• Many qualitative studies use this
technique.
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Nonprobability Sampling
Procedures
• Advantages
– Time
– Money
• Disadvantages
– Nonrandom
– Not able to generalize findings
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Learning Objective Six
Determine Which Sampling Technique To
Use In Various Types Of Research Studies
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Research Studies
• Use voluntary subjects
• Follow the ethics of research
– Subjects must voluntarily agree.
– Subjects may refuse to participate
ممكن يكون المشارك شارك بالبحث مش لاعطاء المعلومة وانما
.لهدية او مكافاة
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Research Data
• Based on voluntary responses from
subjects
• Biased sample occurs if subjects do not
participate.
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Volunteers As Subjects
• Sample selection varies.
– Subjects volunteer for a study.
– Researcher approaches subjects.
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Random Sampling or
Random Assignment
• Random sampling
– Each subject has equal probability of being
included.
• Random assignment
– Procedure to ensure that each subject has
equal chance
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Threefold Randomization Process
• Used for experimental studies
• Helps represent the ideal study procedure
• Steps to ensure the process
– Subjects randomly selected from population
– Subjects randomly assigned to groups
– Experimental treatments randomly assigned
to groups
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Learning Objective Seven
Compare Longitudinal And Cross-Sectional
Studies
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Classification of Research Studies
• Longitudinal
بشوف نفس المشاركبين على فترات
• Cross-sectional
بشوف كل المشاركين بوقت واحد
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Longitudinal Research Study
• Subjects are followed over time.
• A cohort study is one example.
مجموعة اشخاص بينهم اشي متشابه
• Subjects are studied based on
– Similar age group
– Similar background
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Longitudinal Research Study
(cont’d)
• Data are gathered.
– Same subjects
– Several times
– Tells influence of time
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Cross-Sectional Study
• Subjects checked at one point in time
• Data collected from groups of people
• Data may represent differences in
– Ages
– Time periods
– Developmental states
– Important considerations
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Longitudinal Versus
Cross-Sectional Studies
• Longitudinal studies
– Accurate means of studying changes over
time
– Studies take a long time to perform.
• Cross-sectional studies
– Less expensive
– Take less time
– Easier to conduct
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Learning Objective Eight
Enumerate Factors To Be Considered In
Deciding The Size Of The Sample
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Sample Size• No simple rules
• Qualitative studies use much smaller samples than
quantitative studies.
• Factors to consider for sample sizes in quantitative
studies
– Homogeneity of population
Homogenous need less sample size than heterogenous
– Degree of precision desired by the researcher
كل ما زادت الدقة كل ما احتاجت عينة اكبر
– Type of sampling procedure that is used
Non probability need small sample size
Probability need large sample size
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Sample Size (cont’d)
• Central limit theorem
• Sampling distribution of the mean
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Larger Sample Sizes
• Many uncontrolled variables are present.ex; age ,
gender
• Small differences are expected in members.
مثلا لو بدي اربط بين الحمية الغذائية يلي اعطيتها للمشاركين مع نزولهم للوزن
ولاحظنا انه فئة من المشاركين نزلت وزن اكثر وطلع السبب لانهم بمارسوا رياضة معينة
• Population must be divided into subgroups.
• Dropout rate among subjects is expected to be high.
• Statistical tests are used that require a minimum sample
size.
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Power Analysis
• Helps to determine sample size
• May prevent type II error
• Helps to detect statistical significance
:العوامل المؤثرة
1-if power analysis is low that increase type 2 error
2- power analysis increase with increase sample
size
3-alpha level
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Power Analysis (cont’d)
• External funding sources require it.
• Helps determine the optimum sample size
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Nursing Research Studies
• Usually limited to small convenience
samples
• Generalizations to total population difficult
• Small sample sizes warrant replication
studies.
• Similar results from replication help with
generalization.
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Learning Objective Nine
Discuss Sampling Error And
Sampling Bias
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Sampling Bias
• Bias when samples are not carefully selected
• All nonprobability sampling methods have it.
• May occur in probability sampling methods
– Subjects decide not to participate when chosen.
– Final sample is now not representative of population.
سببه الباحث نفسه
Non probability بتكون اعلى ب
في حال انه المشاركين في منهم ما رد Probability ممكن تصير ب
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Sampling Error
• Random fluctuations in data
• Not under the control of the researcher
• Chance variations occur when sample is
chosen.
سببه مش الباحث وانما بالصدفة حدث
نة عن نستدل عليه بانه بيكون في فرق واضح بالافريج تاع العي
الافريج تاع مجتمع الدراسة
..في مثال بالصفحة القادمة
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Avg of population = 71
Avg of samples = 63 – 83 – 71
هون الافريج تاع العينات اشي اكبر من افريج المجتمع واشي اصغر
واشي يساوي
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Learning Objective Ten
Critique The Sampling Procedure
Described In Research Reports
And Articles
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Critiquing the
Population and Samples
• Is the target population identified?
• Is the accessible population identified?
• Was a probability or nonprobability
sampling method used?
• Is the specific sampling method named?
• Is the sampling method described?
• Is the sampling method appropriate for the
study?
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Critiquing the Population and
Samples (cont’d)
• Are the demographic characteristics of the
sample presented?
• Is the sample size adequate?
• Was power analysis used to determine the
sample size?
• Is the sample representative of the
population?
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Critiquing the Population and
Samples (cont’d)
• Are potential sampling biases identified?
• Is subject dropout discussed?