Notes in 07Sampling&DataAnaOnExp

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Published	07/30/2024	The {{c1::sample}} is the reference group that will represent the target population.
Published	07/30/2024	Two major sampling methods:1. {{c1::Probability}} sampling methods2. {{c1::Non-probability}} sampling methods
Published	07/30/2024	In employing {{c1::probability::major type}} sampling methods, everyone has an equal chance to be included in the study.
Published	07/30/2024	In employing {{c1::non-probability::major type}} sampling methods, the investigators choose the participants.
Published	07/30/2024	[[oc1::Simple random sampling]] - equal chance for every unit in pop'n to be chosen as sample[[oc2::Cluster sampling]] - multistage sampling[[oc3::Sys…
Published	07/30/2024	In simple random sampling, a member of the population can have more chance of being chosen as a sample than another member.{{c1::F::T/F}}
Published	07/30/2024	Simple random sampling is commonly used for obtaining samples in {{c1::large::Small/Large}} studies.
Published	07/30/2024	{{c1::Cluster sampling}} involves multistage or successive random sampling of series of units in the population.
Published	07/30/2024	An investigator employed cluster sampling when they randomly selected five physical therapists from three randomly selected cities in three self-chose…
Published	07/30/2024	Systematic sampling is considered equivalent to random sampling, as long as no recurring pattern or particular order exists in the listing.{{c1::T::T/…
Published	07/30/2024	{{c1::Stratified random sampling}} involves identifying relevant population characteristics, and partitioning members of a population into {{c2::homog…
Published	07/30/2024	[[oc1::Convenience sampling]] - subjects are chosen on basis of availability[[oc2::Purposive sampling]] - subjects are hand-picked on basis …
Published	07/30/2024	{{c1::Consecutive sampling}} involves recruiting all patients who meet the inclusion and exclusion criteria as they become available.
Published	07/30/2024	Quota sampling involves using personal networks of the subjects to obtain adequate number of samples.{{c1::F::T/F}}
Published	07/30/2024	Quota sampling requires that each stratum is represented in the same proportion as in the population.{{c1::T::T/F}}
Published	07/30/2024	{{c1::A priori power analysis}} is the estimation of the minimum number of subjects needed to detect a significant difference for an expected effect s…
Published	07/30/2024	A/An {{c1::null hypothesis (Ho)::type of hypothesis}} states that there is no difference or no relationship between the independent and depe…
Published	07/30/2024	A/An {{c1::alternative hypothesis (HA)::type of hypothesis}} states the expected relationship between independent and dependent variabl…
Published	07/30/2024	The {{c1::alpha level}} or the {{c1::level of statistical significace}} is the risk of Type {{c2::I::I/II}} error, or the maximum probability level th…
Published	07/30/2024	The {{c1::confidence interval (CI)}} is the range of values within which a population parameter is estimated to fall, with a specific level of confide…
Published	07/30/2024	An incorrect decision to {{c2::reject::reject/accept}} the Ho is a Type {{c1::I::I/II}} error.
Published	07/30/2024	An incorrect decision to {{c2::accept::reject/accept}} the Ho is a Type {{c1::II::I/II}} error.
Published	07/30/2024	Rejecting the Ho when it is true is a Type {{c1::I::I/II}} error or a False {{c2::Positive::Positive/Negative}}.
Published	07/30/2024	Failure to reject the Ho when it is false is a Type {{c1::II::I/II}} error or a False {{c2::Negative::Positive/Negative}}.
Published	07/30/2024	Parametric statistics require that the assumptions of {{c1::normality}} and {{c1::homogeneity of variance}} are met.
Published	07/30/2024	Examples of Normality Tests:{{c1::Shapiro-Wilk Test}} - more commonly reported{{c1::Kolmogorov-Smirnov Test}}
Published	07/30/2024	The Levene's Test is a test for {{c1::homogeneity of variance}}.
Published	07/30/2024	Non-parametric statistic tests are also called {{c1::distribution-free tests}}.
Published	07/30/2024	{{c1::Non-parametric}} statistics test hypothesis for group comparisons without assumptions of normalcy or variance.
Published	07/30/2024	Many researchers prefer to use parametric tests over non-parametric ones because they are generally considered more powerful.{{c1::T::T/F}}
Published	07/30/2024	STEP 1If Nominal or Ordinal scale: [[oc1::Use non-parametric statistics ]]If Interval or Ratio scale: [[oc1::Check if data are normally dist…
Published	07/30/2024	The {{c1::Student's t-test}} is a parametric statistical test used to compare two means.
Published	07/30/2024	{{c1::Unpaired}} or {{c1::Independent}} t-test is used when the means of two independent groups of subjects are compared.
Published	07/30/2024	{{c1::Paired}} or {{c1::Correlated}} t-test is used when comparing means from correlated samples or repeated measures.
Published	07/30/2024	The {{c1::Analysis of Variance (ANOVA)::parametric test}} is a logical extension of the t-test designed to compare more than two means.
Published	07/30/2024	The Analysis of Variance (ANOVA) is based on the {{c1::F statistic}}.
Published	07/30/2024	{{c1::One-way}} ANOVA is applied when three or more independent group means are compared.
Published	07/30/2024	One-way ANOVA is used in {{c1::between-subjects::between-subjects/within-subjects}} designs.
Published	07/30/2024	{{c1::Repeated measures}} ANOVA is applied when successive measurements of the same group are being compared.
Published	07/30/2024	The {{c1::Mann-Whitney U Test}} is nonparametric statistical test for comparing two independent groups.
Published	07/30/2024	The {{c1::Wilcoxon signed-rank test (T)}} is nonparametric statistical test for comparing two correlated samples (or repeated measures).
Published	07/30/2024	The {{c1::Kruskal-Wallis One-way Analysis of Variance by Ranks (H)}} is a nonparametric statistical procedure for comparing more than two independent …
Published	07/30/2024	The {{c1::Friedman Two-way Analysis of Variance by Ranks (X2r)}} is a nonparametric statistical procedure for repeated measures, comparing more than t…
Published	07/30/2024	Comparison between/among: {{c1::Two-independent groups}}Parametric statistical test: {{c2::Unpaired t-test}}Non-parametric statistical test: {{c2::Man…
Published	07/30/2024	Comparison between/among: {{c1::Two related scores}}Parametric statistical test: {{c2::Paired t-test}}Non-parametric statistical test: {{c2::Wilcoxon …
Published	07/30/2024	Comparison between/among: {{c1::Three or more independent groups}}Parametric statistical test: {{c2::One-way ANOVA (F)}}Non-parametric statistical tes…
Published	07/30/2024	Comparison between/among: {{c1::Three or more related scores}}Parametric statistical test: {{c2::One-way repeated measures (ANOVA) (F)}}Non-parametric…
Published	07/30/2024	The {{c1::effect size}} is the statistical expression of the magnitude of difference between group means. It indicates the degree of separation betwee…
Published	07/30/2024	{{c1::Large::Small/Medium/Large}} effect size- great degree of separation; certain that difference is due to intervention given- with large samples an…
Published	07/30/2024	{{c1::On-protocol analysis}} / {{c1::On-treatment analysis}} / {{c1::Completer analysis}} is a way of handling missing data or protocol deviation by a…
Published	07/30/2024	Completer analysis is usually problematic and would create serious biases.{{c1::T::T/F}}
Published	07/30/2024	In {{c1::intention-to-treat (ITT) analysis}}, data are analyzed according to the original random assignments, regardless of the treatment subjects act…
Published	07/30/2024	ITT analysis guards against potential for bias if dropouts are related to {{c1::outcomes}} or {{c1::group assignment}}.
Published	07/30/2024	ITT analysis {{c1::preserves::preserves/does not preserve}} the original balance of random assignment
Published	07/30/2024	{{c1::Last Observation Carried Forward (LOCF)}} is performed when the subject's last data point before dropping out (i.e., using patient's most recent…
Published	07/30/2024	Can ITT analysis result in an underestimate of treatment effect?{{c1::Y::Y/N}}
Published	07/30/2024	{{c2::Parametric::Parametric/Non-parametric}} statistics accommodate complex clinical designs.
Published	07/30/2024	Parametric statistics are used for {{c1::interval}} or {{c1::ratio}} scale of measurement.
Published	07/30/2024	Non-parametric statistics are used for {{c1::nominal}} or {{c1::ordinal}} scale of measurement.
Published	07/30/2024	Repeated measures ANOVA is used in {{c1::within-subjects::between-subjects/within-subjects}} designs.
Published	07/30/2024	{{c1::Small::Small/Medium/Large}} effect size - not perceptible to human eye; when not under good experimental control- Equivalent to a {{c2::20}}% of…
Published	07/30/2024	{{c1::Medium::Small/Medium/Large}} effect size - visible to the naked eye; one would be aware of the change w/ normal deviation- Equivalent to a {{c2:…
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