Women's Decision-Making And Factors Affecting Their Choice Of ...
Women's Decision-Making And Factors Affecting Their Choice Of ... Women's Decision-Making And Factors Affecting Their Choice Of ...
induction of analysis", and say it is where "the rubber hits the road". The research objectives, researcher's interests, expertise, and skills lead the coding. An important consideration in qualitative data analysis is the conscientious search for, and presentation of negative or deviant cases, i.e., cases that oppose the emerging analysis (Athens 1984; Glaser and Strauss 1965; Henwood and Pidgeon 1993; Lincoln and Guba 1985; Marshall 1985; Mechanic 1989; Phillips 1987). Failure to address negative cases may be a threat to the validity of findings as it introduces holistic bias. Holistic bias is defined as making the data look more patterned than they are (Sandelowski 1986). One of the ways of facilitating the search for negative cases is the use of theoretical sampling as participants are chosen specifically to confirm or refute the findings (Dingwall 1992; Glaser and Strauss 1965; Goodwin and Goodwin 1984a). Deviant cases should be carefully examined to determine how they could be incorporated in the analysis (Secker, Wimbush, Watson et al 1995). The inclusion of negative cases strengthens the credibility of research findings (Silverman 1989), and explains any apparent inconsistencies (Secker, Wimbush, Watson et al 1995). While some authors argue for inclusion of all cases in the analysis (Secker, Wimbush, Watson et al 1995), others contend that the aim should not be to account for all cases, as this would be a rigid goal (Guba and Lincoln 1989; Lincoln and Guba 1985). The analysis, they argue, should account for most of the available data. The most important elements of the analysis therefore are the systematic coding and analysis of the data, inclusion of disconfirming or exceptional cases, and the modification of the analysis in the light of contrary evidence (Murphy, Dingwall, Greatbatch et al 1998). Such an approach to analysis has been likened to the careful search for falsifying evidence in science, which adds weight to the truth claims of an investigation. Phillips (1987) argues 93
that while such an approach can never guarantee truth, it supports the elimination of error. It has been argued that since qualitative researchers are committed to making public the private lives of participants, it is ironical that their own methods of analysis remain private and unavailable for public inspection (Chenail 1995; Constas 1992; Harries-Jones 1995). Constas contends that the provision of detailed descriptions of the development of categories will help dissipate the notion of qualitative research being half science and half chimera, while the absence of such information may vitiate the clarity of a given empirical presentation. Analytical rigour in qualitative research is defined as an attempt to make data and the schemes used to organise it as public and replicable as possible (Denzin 1978). Additionally, Chenail (1995) argues that in a well-done qualitative study, the reader should have many opportunities to examine the particulars of the inquiry, such as, the processing and analysing of the data. He maintains that it is in this spirit of openness that trust is built between the researcher and the reader. Summary Chapter 4 has discussed the general theory behind the methodology of qualitative research. The main positive features of qualitative research were identified as, firstly, the ability to access participants' definitions and interpretations (Crabtree and Miller 1991; de Vries et al 1992; Jensen 1989; Paget 1983; West 1990), thus helping the investigator to be part of the participants' world. Secondly, qualitative research is useful in studying thoughts, feelings, intentions, and experiences which otherwise would not be open to study (McCracken 1988; Patton 1980; Silverman 1993; Secker et al 1995). Another 94
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- Page 47 and 48: Chapter 3: Systematic review of fac
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- Page 53 and 54: Cochrane Database of Systematic rev
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- Page 75 and 76: known? What roles do values play in
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induction of analysis", and say it is where "the rubber hits the road". The<br />
research objectives, researcher's interests, expertise, and skills lead the coding.<br />
An important consideration in qualitative data analysis is the conscientious<br />
search for, and presentation of negative or deviant cases, i.e., cases that oppose the<br />
emerging analysis (Athens 1984; Glaser and Strauss 1965; Henwood and Pidgeon<br />
1993; Lincoln and Guba 1985; Marshall 1985; Mechanic 1989; Phillips 1987).<br />
Failure to address negative cases may be a threat to the validity of findings as it<br />
introduces holistic bias. Holistic bias is defined as making the data look more<br />
patterned than they are (Sandelowski 1986). One of the ways of facilitating the<br />
search for negative cases is the use of theoretical sampling as participants are<br />
chosen specifically to confirm or refute the findings (Dingwall 1992; Glaser and<br />
Strauss 1965; Goodwin and Goodwin 1984a). Deviant cases should be carefully<br />
examined to determine how they could be incorporated in the analysis (Secker,<br />
Wimbush, Watson et al 1995). The inclusion of negative cases strengthens the<br />
credibility of research findings (Silverman 1989), and explains any apparent<br />
inconsistencies (Secker, Wimbush, Watson et al 1995).<br />
While some authors argue for inclusion of all cases in the analysis (Secker,<br />
Wimbush, Watson et al 1995), others contend that the aim should not be to<br />
account for all cases, as this would be a rigid goal (Guba and Lincoln 1989;<br />
Lincoln and Guba 1985). The analysis, they argue, should account for most of the<br />
available data. The most important elements of the analysis therefore are the<br />
systematic coding and analysis of the data, inclusion of disconfirming or<br />
exceptional cases, and the modification of the analysis in the light of contrary<br />
evidence (Murphy, Dingwall, Greatbatch et al 1998). Such an approach to<br />
analysis has been likened to the careful search for falsifying evidence in science,<br />
which adds weight to the truth claims of an investigation. Phillips (1987) argues<br />
93
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