{"id":28012,"date":"2023-05-24T10:07:19","date_gmt":"2023-05-24T13:07:19","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/?p=28012"},"modified":"2023-05-24T10:07:21","modified_gmt":"2023-05-24T13:07:21","slug":"sampling-bias","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/lt\/atrankos-saliskumas\/","title":{"rendered":"Problema, vadinama atrankos \u0161ali\u0161kumu"},"content":{"rendered":"<p>Nepriklausomai nuo naudojamos metodikos ar tiriamos disciplinos, tyr\u0117jai turi u\u017etikrinti, kad jie naudot\u0173 reprezentatyvias imtis, atspindin\u010dias tiriamos populiacijos charakteristikas. \u0160iame straipsnyje bus nagrin\u0117jama imties \u0161ali\u0161kumo s\u0105voka, jo skirtingos r\u016b\u0161ys ir taikymo b\u016bdai bei geriausia praktika, kaip suma\u017einti jo poveik\u012f.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Kas yra atrankos \u0161ali\u0161kumas?<\/h2>\n\n\n\n<p>Imties \u0161ali\u0161kumas - tai situacija, kai tam tikri populiacijos individai ar grup\u0117s \u012f imt\u012f patenka da\u017eniau nei kiti, tod\u0117l imtis yra \u0161ali\u0161ka arba nereprezentatyvi. Taip gali atsitikti d\u0117l \u012fvairi\u0173 prie\u017eas\u010di\u0173, pavyzd\u017eiui, d\u0117l neatsitiktini\u0173 imties sudarymo metod\u0173, sav\u0119s atrankos \u0161ali\u0161kumo arba tyr\u0117jo \u0161ali\u0161kumo.<\/p>\n\n\n\n<p>Kitaip tariant, atrankos \u0161ali\u0161kumas gali pakenkti tyrimo rezultat\u0173 pagr\u012fstumui ir apibendrinamumui, nes imt\u012f i\u0161kreipia tam tikr\u0173 savybi\u0173 ar po\u017ei\u016bri\u0173, kurie gali neatitikti didesn\u0117s populiacijos.&nbsp;<\/p>\n\n\n\n<p>Idealiu atveju visus apklausos dalyvius reikia atrinkti atsitiktine tvarka. Ta\u010diau praktikoje gali b\u016bti sunku atlikti atsitiktin\u0119 dalyvi\u0173 atrank\u0105 d\u0117l toki\u0173 apribojim\u0173, kaip i\u0161laidos ir respondent\u0173 prieinamumas. Net jei duomen\u0173 nerenkate atsitiktine tvarka, labai svarbu \u017einoti apie galimus \u0161ali\u0161kumus, kurie gali b\u016bti j\u016bs\u0173 duomenyse.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Kai kurie imties atrankos \u0161ali\u0161kumo pavyzd\u017eiai:<\/h3>\n\n\n\n<ol>\n<li><strong>Savanori\u0173 \u0161ali\u0161kumas<\/strong>: Dalyvi\u0173, kurie savanori\u0161kai dalyvauja tyrime, charakteristikos gali skirtis nuo savanori\u0161kai nedalyvaujan\u010di\u0173, tod\u0117l imtis gali b\u016bti nereprezentatyvi.<\/li>\n\n\n\n<li><strong>Neatsitiktin\u0117 atranka<\/strong>: Jei tyr\u0117jas atrenka dalyvius tik i\u0161 tam tikr\u0173 vietovi\u0173 arba atrenka tik tam tikromis savyb\u0117mis pasi\u017eymin\u010dius dalyvius, imtis gali b\u016bti neobjektyvi.<\/li>\n\n\n\n<li><strong>I\u0161gyvenimo \u0161ali\u0161kumas<\/strong>: Taip atsitinka, kai \u012f imt\u012f \u012ftraukiami tik tie asmenys, kurie i\u0161gyveno arba kuriems pavyko tam tikroje situacijoje, ta\u010diau ne\u012ftraukiami tie, kurie nei\u0161gyveno arba kuriems nepavyko.<\/li>\n\n\n\n<li><strong>Patogus m\u0117gini\u0173 \u0117mimas<\/strong>: \u0160io tipo atranka apima lengvai prieinam\u0173 dalyvi\u0173, pavyzd\u017eiui, esan\u010di\u0173 netoliese, arba atsakiusi\u0173j\u0173 \u012f internetin\u0119 apklaus\u0105 atrank\u0105, kuri gali neatspind\u0117ti didesn\u0117s populiacijos.<\/li>\n\n\n\n<li><strong>Patvirtinimo \u0161ali\u0161kumas<\/strong>: Tyr\u0117jai gali nes\u0105moningai ar s\u0105moningai pasirinkti dalyvius, kurie patvirtina j\u0173 hipotez\u0119 ar tyrimo klausim\u0105, tod\u0117l rezultatai gali b\u016bti neobjektyv\u016bs.<\/li>\n\n\n\n<li><strong>Hawthorne efektas<\/strong>: Dalyviai, \u017einodami, kad yra tiriami ar stebimi, gali keisti savo elges\u012f ar atsakymus, tod\u0117l rezultatai gali b\u016bti nereprezentatyv\u016bs.<\/li>\n<\/ol>\n\n\n\n<p>&nbsp;Jei \u017einote apie \u0161iuos \u0161ali\u0161kumus, galite \u012f juos atsi\u017evelgti analiz\u0117je, kad gal\u0117tum\u0117te atlikti \u0161ali\u0161kumo korekcij\u0105 ir geriau suprasti, kokiai populiacijai atstovauja j\u016bs\u0173 duomenys.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Imties nuokrypio tipai<\/h2>\n\n\n\n<ul>\n<li><strong>Atrankos \u0161ali\u0161kumas<\/strong>: pasitaiko, kai imtis n\u0117ra reprezentatyvi populiacijai.<\/li>\n\n\n\n<li><strong>Matavimo paklaida<\/strong>: pasitaiko, kai surinkti duomenys yra netiksl\u016bs arba nei\u0161sam\u016bs.<\/li>\n\n\n\n<li><strong>Ataskait\u0173 teikimo \u0161ali\u0161kumas<\/strong>: pasitaiko, kai respondentai pateikia netiksli\u0105 arba nei\u0161sami\u0105 informacij\u0105.<\/li>\n\n\n\n<li><strong>Neatsakymo \u0161ali\u0161kumas<\/strong>kai dalis populiacijos nari\u0173 neatsako \u012f apklausos klausimus ir d\u0117l to gaunama nereprezentatyvi imtis.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Imties nuokrypio prie\u017eastys<\/h2>\n\n\n\n<ol>\n<li><strong>Patogus m\u0117gini\u0173 \u0117mimas<\/strong>: imties atranka remiantis patogumu, o ne moksliniu metodu.<\/li>\n\n\n\n<li><strong>Savaranki\u0161kos atrankos \u0161ali\u0161kumas<\/strong>: \u012f apklaus\u0105 \u012ftraukiami tik tie, kurie joje dalyvauja savanori\u0161kai, o tai gali neatspind\u0117ti visos populiacijos.<\/li>\n\n\n\n<li><strong>Imties r\u0117mo nuokrypis<\/strong>: kai im\u010diai atrinkti naudojama atrankos sistema n\u0117ra reprezentatyvi populiacijai.<\/li>\n\n\n\n<li><strong>I\u0161gyvenimo \u0161ali\u0161kumas<\/strong>: kai tyrime dalyvauja tik tam tikri populiacijos nariai ir d\u0117l to gaunama nereprezentatyvi imtis. Pavyzd\u017eiui, jei tyr\u0117jai apklausia tik gyvus \u017emones, jie gali negauti informacijos i\u0161 \u017emoni\u0173, kurie mir\u0117 prie\u0161 atliekant tyrim\u0105.<\/li>\n\n\n\n<li><strong>Atrankos \u0161ali\u0161kumas d\u0117l \u017eini\u0173 tr\u016bkumo<\/strong>: neatpa\u017e\u012fsta kintamumo \u0161altini\u0173, d\u0117l kuri\u0173 \u012fver\u010diai gali b\u016bti neobjektyv\u016bs.<\/li>\n\n\n\n<li><strong>Imties nuokrypis d\u0117l imties administravimo klaid\u0173<\/strong>: nesinaudojama tinkama ar gerai veikian\u010dia imties sistema arba atsisakoma dalyvauti tyrime, tod\u0117l imtis atrenkama neobjektyviai.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Imties atrankos paklaida klinikiniuose tyrimuose<\/h2>\n\n\n\n<p>Klinikiniais tyrimais siekiama i\u0161bandyti naujo gydymo ar vaist\u0173 veiksmingum\u0105 tam tikroje populiacijoje. Jie yra esmin\u0117 vaist\u0173 k\u016brimo proceso dalis ir jais nustatoma, ar gydymas yra saugus ir veiksmingas, prie\u0161 pateikiant j\u012f visuomenei apskritai. Ta\u010diau klinikiniams tyrimams taip pat b\u016bdingas atrankos \u0161ali\u0161kumas.<\/p>\n\n\n\n<p>Atrankos \u0161ali\u0161kumas atsiranda tada, kai tyrimui naudojama imtis neatspindi populiacijos, kuri\u0105 reikia reprezentuoti. Klinikini\u0173 tyrim\u0173 atveju atrankos \u0161ali\u0161kumas gali pasireik\u0161ti, kai dalyviai yra pasirenkami dalyvauti atrankos b\u016bdu arba atrenkami patys.<\/p>\n\n\n\n<p>Tarkime, kad farmacijos bendrov\u0117 atlieka klinikin\u012f tyrim\u0105, siekdama patikrinti naujo vaisto nuo v\u0117\u017eio veiksmingum\u0105. Ji nusprend\u017eia rinkti tyrimo dalyvius per skelbimus ligonin\u0117se, klinikose ir v\u0117\u017eio paramos grup\u0117se, taip pat per internetines parai\u0161kas. Ta\u010diau j\u0173 renkama imtis gali b\u016bti \u0161ali\u0161ka, nes joje gali dalyvauti tie, kurie yra labiau motyvuoti dalyvauti tyrime arba serga tam tikro tipo v\u0117\u017eiu. D\u0117l to gali b\u016bti sunku tyrimo rezultatus apibendrinti didesnei populiacijai.<\/p>\n\n\n\n<p>Siekdami suma\u017einti atrankos \u0161ali\u0161kum\u0105 klinikiniuose tyrimuose, tyr\u0117jai turi taikyti grie\u017etus \u012ftraukimo ir ne\u012ftraukimo kriterijus ir atsitiktin\u0117s atrankos procesus. Taip bus u\u017etikrinta, kad tyrimui atrinkt\u0173 dalyvi\u0173 imtis b\u016bt\u0173 reprezentatyvi didesnei populiacijai, tod\u0117l surinkt\u0173 duomen\u0173 \u0161ali\u0161kumas bus kuo ma\u017eesnis.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Problemos, kylan\u010dios d\u0117l atrankos \u0161ali\u0161kumo<\/h2>\n\n\n\n<p>Imties nuokrypis yra problemi\u0161kas, nes gali b\u016bti, kad i\u0161 imties apskai\u010diuota statistika yra sistemingai klaidinga. D\u0117l to atitinkamas populiacijos parametras gali b\u016bti sistemingai pervertintas arba nepakankamai \u012fvertintas. Tai pasitaiko praktikoje, nes prakti\u0161kai ne\u012fmanoma u\u017etikrinti tobulo atsitiktinumo imant imt\u012f.<\/p>\n\n\n\n<p>Jei i\u0161kraipymo laipsnis yra nedidelis, imt\u012f galima laikyti pagr\u012fstu atsitiktin\u0117s imties prilyginimu. Be to, jei imtis labai nesiskiria matuojamu dyd\u017eiu, tada i\u0161kreipta imtis vis tiek gali b\u016bti pagr\u012fstas \u012fvertis.<\/p>\n\n\n\n<p>Nors kai kurie asmenys gali s\u0105moningai naudoti neobjektyvi\u0105 imt\u012f, kad gaut\u0173 klaidinan\u010dius rezultatus, da\u017eniau neobjektyvi imtis tiesiog atspindi sunkumus gauti tikrai reprezentatyvi\u0105 imt\u012f arba matavimo ar analiz\u0117s proceso neobjektyvum\u0105.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Ekstrapoliacija: vir\u0161ijama riba<\/h2>\n\n\n\n<p>Statistikoje i\u0161vad\u0173 darymas apie ka\u017ek\u0105, kas i\u0161eina u\u017e duomen\u0173 rib\u0173, vadinamas ekstrapoliacija. Viena i\u0161 ekstrapoliacijos form\u0173 yra i\u0161vados darymas i\u0161 \u0161ali\u0161kos imties: kadangi taikant imties sudarymo metod\u0105 sistemingai ne\u012ftraukiamos tam tikros nagrin\u0117jamos populiacijos dalys, i\u0161vados taikomos tik atrinktai subpopuliacijai.<\/p>\n\n\n\n<p>Ekstrapoliacija taip pat atsiranda, jei, pavyzd\u017eiui, universiteto student\u0173 imtimi pagr\u012fsta i\u0161vada taikoma vyresnio am\u017eiaus suaugusiesiems arba suaugusiesiems, turintiems tik 8 klasi\u0173 i\u0161silavinim\u0105. Ekstrapoliacija yra da\u017ena statistikos taikymo ar ai\u0161kinimo klaida. Kartais d\u0117l to, kad sunku arba ne\u012fmanoma gauti ger\u0173 duomen\u0173, ekstrapoliacija yra geriausia, k\u0105 galime padaryti, ta\u010diau visada reikia \u012f j\u0105 \u017ei\u016br\u0117ti bent su trupu\u010diu druskos, o da\u017enai ir su didele neapibr\u0117\u017etumo doze.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">I\u0161 mokslo \u012f pseudomoksl\u0105<\/h2>\n\n\n\n<p><a href=\"https:\/\/en.wikipedia.org\/wiki\/Sampling_bias\">Kaip minima Vikipedijoje<\/a>, pavyzdys, kaip gali egzistuoti \u0161ali\u0161kumo ne\u017einojimas, yra pla\u010diai paplit\u0119s santykio (dar vadinamo kartus poky\u010diu), kaip biologinio skirtumo mato, naudojimas. Kadangi lengviau pasiekti didel\u012f santyk\u012f su dviem ma\u017eais skai\u010diais, turin\u010diais tam tikr\u0105 skirtum\u0105, ir santykinai sunkiau pasiekti didel\u012f santyk\u012f su dviem dideliais skai\u010diais, turin\u010diais didesn\u012f skirtum\u0105, lyginant santykinai didelius skaitinius matavimus gali b\u016bti nepasteb\u0117ti dideli reik\u0161mingi skirtumai.&nbsp;<\/p>\n\n\n\n<p>Kai kas tai vadina \"demarkacijos \u0161ali\u0161kumu\", nes naudojant santyk\u012f (dalijim\u0105), o ne skirtum\u0105 (atimt\u012f), analiz\u0117s rezultatai i\u0161 mokslo virsta pseudomokslu.<\/p>\n\n\n\n<p>Kai kuriose imtyse naudojamas neobjektyvus statistinis planas, kuris vis d\u0117lto leid\u017eia \u012fvertinti parametrus. Pavyzd\u017eiui, JAV Nacionalinis sveikatos statistikos centras daugelyje savo nacionalinio masto apklaus\u0173 s\u0105moningai sudaro per dideles ma\u017eum\u0173 gyventoj\u0173 imtis, kad gaut\u0173 pakankamai tikslius \u012fver\u010dius \u0161iose grup\u0117se.<\/p>\n\n\n\n<p>Norint gauti tinkamus vis\u0173 etnini\u0173 grupi\u0173 \u012fver\u010dius, \u0161iuose tyrimuose reikia naudoti imties svorius. Jei laikomasi tam tikr\u0173 s\u0105lyg\u0173 (vis\u0173 pirma, jei svoriai apskai\u010diuojami ir naudojami teisingai), \u0161ios imtys leid\u017eia tiksliai \u012fvertinti populiacijos parametrus.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Geriausia atrankos \u0161ali\u0161kumo ma\u017einimo praktika<\/h2>\n\n\n\n<p>Labai svarbu pasirinkti tinkam\u0105 atrankos metod\u0105, kad gauti duomenys tiksliai atspind\u0117t\u0173 tiriam\u0105j\u0105 populiacij\u0105.<\/p>\n\n\n\n<ol>\n<li><strong>Atsitiktin\u0117s atrankos metodai<\/strong>: Taikant atsitiktin\u0117s atrankos metodus padid\u0117ja tikimyb\u0117, kad imtis yra reprezentatyvi populiacijai. \u0160is metodas padeda u\u017etikrinti, kad imtis b\u016bt\u0173 kuo labiau reprezentatyvi tiriamajai populiacijai, tod\u0117l ma\u017eiau tik\u0117tina, kad joje bus \u0161ali\u0161kumo.<\/li>\n\n\n\n<li><strong>Imties dyd\u017eio apskai\u010diavimas<\/strong>: Imties dydis tur\u0117t\u0173 b\u016bti apskai\u010diuojamas taip, kad b\u016bt\u0173 galima patikrinti statisti\u0161kai reik\u0161mingas hipotezes. Kuo didesn\u0117 imtis, tuo geriau atspindima populiacija.<\/li>\n\n\n\n<li><strong>Tendencij\u0173 analiz\u0117<\/strong>: Ie\u0161koti alternatyvi\u0173 duomen\u0173 \u0161altini\u0173 ir analizuoti bet kokias pasteb\u0117tas tendencijas duomenyse, kurie gali b\u016bti nepasirinkti.<\/li>\n\n\n\n<li><strong>\u0160ali\u0161kumo tikrinimas<\/strong>: Reik\u0117t\u0173 steb\u0117ti \u0161ali\u0161kumo atvejus, kad b\u016bt\u0173 galima nustatyti sisteming\u0105 konkre\u010di\u0173 duomen\u0173 ta\u0161k\u0173 ne\u012ftraukim\u0105 ar per didel\u012f \u012ftraukim\u0105.<\/li>\n<\/ol>\n\n\n\n<p><strong>Atkreipkite d\u0117mes\u012f \u012f pavyzd\u017eius<\/strong><\/p>\n\n\n\n<p>Atliekant tyrimus labai svarbu atsi\u017evelgti \u012f imties paklaid\u0105. Nepriklausomai nuo naudojamos metodikos ar tiriamos disciplinos, tyr\u0117jai turi u\u017etikrinti, kad jie naudot\u0173 reprezentatyvias imtis, kurios atspind\u0117t\u0173 tiriamos populiacijos charakteristikas.<\/p>\n\n\n\n<p>Rengiant mokslinius tyrimus labai svarbu atkreipti d\u0117mes\u012f \u012f imties atrankos proces\u0105, taip pat \u012f metodik\u0105, taikom\u0105 duomenims i\u0161 imties rinkti. Siekiant u\u017etikrinti, kad tyrim\u0173 rezultatai b\u016bt\u0173 pagr\u012fsti ir patikimi, tod\u0117l didesn\u0117 tikimyb\u0117, kad jie tur\u0117s \u012ftakos politikai ir praktikai, reik\u0117t\u0173 taikyti geriausi\u0105 praktik\u0105, pavyzd\u017eiui, atsitiktin\u0117s atrankos metodus, imties dyd\u017eio apskai\u010diavim\u0105, tendencij\u0173 analiz\u0119 ir \u0161ali\u0161kumo tikrinim\u0105.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Ak\u012f traukian\u010dios mokslin\u0117s infografikos per kelias minutes<\/h2>\n\n\n\n<p><a href=\"http:\/\/mindthegraph.com\/\">Mind the Graph<\/a> yra galingas internetinis \u012frankis mokslininkams, kuriems reikia kurti auk\u0161tos kokyb\u0117s mokslin\u0119 grafik\u0105 ir iliustracijas. \u0160i platforma yra patogi ir prieinama \u012fvairaus lygio technini\u0173 \u017eini\u0173 turintiems mokslininkams, tod\u0117l ji yra idealus sprendimas mokslininkams, kuriems reikia kurti grafik\u0105 savo publikacijoms, pristatymams ir kitai mokslin\u0117s komunikacijos med\u017eiagai.<\/p>\n\n\n\n<p>Nesvarbu, ar dirbate gyvyb\u0117s, fizini\u0173 ar in\u017einerijos moksl\u0173 srityje, Mind the Graph si\u016blo daugyb\u0119 \u0161altini\u0173, kurie pad\u0117s ai\u0161kiai ir vizualiai patraukliai pateikti mokslini\u0173 tyrim\u0173 rezultatus.<\/p>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" loading=\"lazy\" width=\"600\" height=\"338\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2022\/10\/r3qiu0qenda-3.gif\" alt=\"\" class=\"wp-image-25130\"\/><\/figure><\/div>\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"is-layout-flex wp-block-buttons\">\n<div class=\"wp-block-button aligncenter\"><a class=\"wp-block-button__link has-background wp-element-button\" href=\"https:\/\/mindthegraph.com\/app\/offer-trial\" style=\"border-radius:50px;background-color:#dc1866\" target=\"_blank\" rel=\"noreferrer noopener\">Nemokamai prad\u0117kite kurti infografik\u0105<\/a><\/div>\n<\/div>\n\n\n\n<div style=\"height:44px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>","protected":false},"excerpt":{"rendered":"<p>Atrankos \u0161ali\u0161kumas yra labai svarbus aspektas atliekant tyrimus tokiose disciplinose kaip statistika, socialiniai mokslai ir epidemiologija. <\/p>","protected":false},"author":38,"featured_media":28013,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[959,28],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.9 - 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